DHQ: Digital Humanities Quarterly
2015
Volume 9 Number 3
2015 9.3  |  XML |  Discuss ( Comments )

Comparative rates of text reuse in classical Latin hexameter poetry

Kyle Gervais <kgervai2_at_uwo_dot_ca>, University of Western Ontario
Wei Lin <linw_at_ohio_dot_edu>, Ohio University

Abstract

This paper presents a quantitative picture of the interactions between poets in the Latin hexameter tradition. The freely available Tesserae website (tesserae.caset.buffalo.edu) automatically searches pairs of texts in a corpus of over 300 works of Latin literature in order to identify instances where short passages share two or more repeated lexemes. We use Tesserae to survey relative rates of text reuse in 24 Latin hexameter works written from the 1st century BCE to the 6th century CE. We compare the quantitative information about text reuse provided by Tesserae to the scholarly tradition of qualitative discussion of allusion by Latinists.

The detection and interpretation of allusion currently represent the dominant mode of study of Latin poetry.[1] The typical goal of intertextual study is to describe how links between texts affect the meaning of both the specific passages that contain them and the poems as a whole. Although intertextual associations may be signalled in many different ways (including similarity of action, character, or theme), verbal repetition, or text reuse, is the best studied and often the strongest type of signal. Philogical commentaries, copiously detailed collections of information on individual books of Latin epic poems, have been the traditional means for Latin poetry scholars to collect and present interpretations based on studies of text reuse. An example from Parkes’ recent commentary on the fourth book of Statius’ Thebaid demonstrates the practice of translating the evidence of verbal repetition into interpretation:

[Statius, Thebaid 4.260] audaci Martis percussus amore ["struck by a bold desire for warfare"[2]]: … The collocation percussus amore ["struck by a desire"] is not uncommon (compare e.g. Verg. G. 2.476, Hor. Epod. 11.2 amore percussum, and Nem. Cyn. 99) but Statius may be specifically recalling the ephebe Euryalus’ reaction to Nisus’ planned expedition at Verg. A. 9.197: magno laudum percussus amore ["struck by a great desire for glory"]…. Like Parthenopaeus, Euryalus is eager to brave danger for the chance of glory (A. 9.205–6), with similarly fatal results.  [Parkes 2012, 164]

This exemplary note builds its interpretation on the evidence of the repetition of two key lexemes, the verb percutio ("I strike") and the noun amor ("desire").[3] The cooccurence of these lexemes in the Statian passage signifies for most readers a link to the passage from Vergil. The discovery of such verbal links has been facilitated in recent years by digital tools such as the freely available Tesserae web interface (tesserae.caset.buffalo.edu), a search program developed by Neil Coffee and a team at the University at Buffalo. Tesserae allows users to search pairs of texts (an earlier "source" text paired with a later "target" text) in a corpus of over 300 poetic and prose works, in order to discover every instance where short passages (either lines of verse or grammatical periods) share two or more repeated lexemes. Thus, a Tesserae search that pairs the Thebaid with the Aeneid permits the user to discover the allusion discussed by Parkes by identifying the repetition of the lexemes percutio and amor. The Tesserae scoring system signals the potential interpretive significance of the match by assigning it a high score, 8 out of approximately 11.[4]
In addition, Tesserae identifies a second potential match (score = 7) between Thebaid 4.260 and another passage from the Aeneid:

Statius, Thebaid 4.260 prosilit audaci Martis percussus amore ("Parthenopaeus leapt up, struck by a bold desire for warfare").

Vergil, Aeneid 7.550 accendamque animos insani Martis amore ("I’ll inflame their minds with a desire for mad warfare").

The words in the Aeneid are spoken by Allecto, a demon of the underworld, and we may thus once more translate this evidence of verbal repetition provided by Tesserae into literary interpretation.[5] Parthenopaeus’ desire to fight in the Theban war in Statius is not only fatal, like the desire of Vergil’s Euryalus to participate in Nisus’ expedition; it is also infernal, like the war provoked by Vergil’s Allecto. This is consistent with Statius’ characterization of the Theban war as destructive and impious throughout the Thebaid. Such new avenues for specific intertextual interpretation are the typical results of Tesserae searches. Previous examples of comparable results can be found in a study of verbal reuse of Vergil’s Aeneid by the epic poet Lucan [Coffee et al. 2012]. Coffee et al. hand-ranked all Tesserae results from a comparison of Lucan Bellum Civile 1 (target) and Vergil’s Aeneid (source) on a 5–point scale of interpretive significance. They concluded that the Tesserae search had identified 25% more interpretively significant instances of text reuse than the standard philological commentaries on Bellum Civile 1 [Roche 2009] [Viansino 1995].
The interpretation of specific allusions relies partly on the characterization of the overall intertextual relationship between texts, which is often hampered by a haphazard approach to gathering data. This paper presents a more consistent, quantitative picture of the interactions between poets in the Latin hexameter tradition. We use Tesserae to generate a statistical analysis of relative rates of text reuse in 24 Latin hexameter works written from the 1st century BCE to the 6th century CE. We then compare the quantitative information about text reuse provided by Tesserae to the scholarly tradition of qualitative discussion of allusion by Latinists. Statistical analyses of certain aspects of Latin poetry are not new. Drobisch’s studies beginning the 1860s represented the birth of the modern statistical studies of metrical aspects of the epic hexameter, a tradition which has reached a high-water mark in the recent work of Ceccarelli [Ceccarelli 2008] [Drobisch 1866]. Counts of individual lexical items in Latin poetry, usually in an effort to determine whether particular words should be considered "poetic" or "unpoetic", are best represented by the tradition of Axelson’s work [Watson 1985] [Axelson 1945]. Yet scholars have not typically evaluated instances of verbal reuse in quantitative terms, as it has simply not been possible for human readers to count such instances accurately. The speed, consistency, and comprehensiveness of Tesserae searches now enable the interpreter to quantify the reuse of phrases on a scale beyond the capacities of ordinary human reading.
Powerful and productive as the Tesserae interface is, the following limitations must be clearly understood. They bear on analysis of specific passages, and to a lesser extent on our large-scale study:
  1. Text reuse does not give the full, complex picture of intertextuality in Latin hexameter, where allusions may be signalled by similarity of action, character, theme, and so on.
  2. Not all text reuse features the repetition of two or more lexemes. At its current stage of development, Tesserae focuses on pairs of lexemes and so cannot reliably identify repetition of single significant words. It would accordingly be unable to flag, for example, the very common word arma ("warfare"). This word takes on a new intertextual significance in poems written after the Aeneid, a foundational epic poem that begins with the words Arma uirumque cano… ("I sing of arms and the man…") [Fowler 1997, 20]. There is accordingly need of a sensitive human interpreter to uncover the metapoetic significance, for example, of the opening word of Ovid’s Amores, Arma graui numero uiolentaque bella parabam / edere… ("I was beginning to sing of arms and violent wars in a serious meter...")
  3. The Latin poets wrote for an audience of Roman elites that were literate in Greek [Hutchinson 2013], and so created numerous translingual calques on Greek phrases. To remain with the example of Vergil, the Aeneid adapts numerous lines and phrases from Homer’s Iliad and Odyssey. Some foundational studies have uncovered these calques using traditional philological methods [Knauer 1964] [Nelis 2001], but such studies have not been pursued systematically across the Latin corpus. A feature of Tesserae currently in development searches for such translingual allusions between Latin and Greek poetry, but is not yet a reliable tool.
  4. Repetitions with verbal variations that seem slight to a human reader are determinative for Tesserae. For example, Tesserae will locate the following correspondence based on the repetition of the lexemes Acheron and moueo:

    Silius Italicus, Punica 2.536 quis Acheronta moues, flammam immanesque chelydros… ("[The weapons] with which you rouse the underword — flame and monstrous serpents…").

    Vergil, Aeneid 7.312 flectere si nequeo superos, Acheronta mouebo ("If I cannot sway the gods above, I will rouse the underworld").

    But Tesserae cannot yet locate the equally significant allusion:

    Silius Italicus, Punica 2.367 …aeternum famulam liberque Acheronta uidebo ("…An eternal slave; I will see the underworld as a free man").

    The change from the verb moueo ("I move") to uideo ("I see") means the phrase no longer contains two repeated lexemes. This means that Tesserae will inevitably miss some of the variations on a verbal motif that form a component of the Latin poets’ creative art. That said, the majority of allusions identified via traditional reading are repeated phrases. So though Tesserae cannot uncover allusions of this type, the majority of such allusions are typically missed by human readers as well.
  5. The Tesserae scoring system provides a measure of interpretive significance that correlates with human-generated measures [Forstall et al. 2014]. Numerous passages of Latin poetry that human readers have traditionally thought of as linked through allusion are also high-scoring lexeme matches, and these correspondences form the basis for scholarly confidence in the scoring system. Yet the score assigned to any given lexeme match does not generate by itself the kind of sensitive assessment of significance that a scholarly reader of Latin poetry brings to the identification of parallel passages. In order to be significant, the allusion must be placed in a larger scholarly narrative of the passage’s compositional goals. A human reader must be able to make a plausible interpretation of the allusion before it can be recognized as an allusion rather a chance repetition [Farrell 2005]. Tesserae’s usefulness comes in discovering potential allusive connections through lexeme matching and ordering them by the rarity and proximity of the paired lexemes. Subjective interpretation of these connections is still required for any meaning-making exercise [Drucker 2009].
Within these acknowledged limitations, Tesserae can be an extraordinarily powerful tool for representing the large-scale reuse of text in a literary tradition. Focusing as it does on repetition of phrases, the most commonly studied marker of allusion, Tesserae can provide a large-scale view of intertextual relationships that models traditional scholarly practice. The program can generate provisional answers to questions of particular relevance to the study of the Latin hexameter genre. Tesserae enables us to undertake the first large-scale statistical study of intertextuality in classical literary studies. Classicists have used new digital tools since their inception, and several techniques of digital text analysis were pioneered on Latin literary corpora, from Fr. Busa’s Index Thomisticus to the Packard concordance of Livy [Bodard and Mahony 2010] [McCarty 2005]. Studies of intertextuality, however, have generally been confined to pairs or very small sets of texts, and have traditionally relied on broad but subjective classification of intertextual data (synonyms, similar motifs, images, etc.), rather than objective parameters such as lexeme matches, lexeme frequency, and lexeme proximity. The Tesserae scoring system, however, represents the first opportunity to quantify the study of intertextuality using a large set of poems and objective parameters. Our object of study is the entire super-genre of Latin hexameter poetry, in which we privilege the system of relationships between texts rather than any integral text itself.
Latin poetry scholars have traditionally divided the "super-genre" of hexameter into several subgenres, including satire, epic, and didactic [Hutchinson 2013]. Is it possible to quantify the verbal cohesiveness and distinctiveness of these genres? What other general factors affect text reuse across the entire hexameter tradition? Can the well-known influence of Vergil and Ovid on their epic successors be quantified? In particular, can it be determined how frequently one predecessor’s text is reused compared to another’s? For example, is Statius’ Thebaid more "Vergilian" in terms of text reuse than another contemporary epic poem, Silius Italicus’ Punica? Most specialist readers of these Flavian epic poets would correctly guess that the answer is no, but would perhaps not be so confident in making assertions about the two poems’ relative rates of reuse of other, earlier poets such as Ovid, Lucan, or Manilius. Which works in the classical hexameter tradition provide the most significant verbal resources for the hexameter epics of late antiquity? This study offers preliminary answers to such questions from a quantitative perspective by surveying the relative rates of text reuse in 24 Latin hexameter works written from the 1st century BCE to the 6th century CE.

2. METHODS

a. Text Selection

Our analysis included every possible source–target pair from a set of 24 Latin hexameter texts written from the 1st century BCE to the 6th century CE (Table 1[6]). This set included every hexameter text available on the Tesserae website,[7] excluding hexameter poems from polymetric collections (such as Catullus’ poems or Statius’ Silvae), hexameter works with non-hexameter prefaces (such as Claudian’s In Rufinum[8]), and four very short minor texts.[9]

b. Data collection and scoring

Using the Tesserae Batch Processing option (http://tess-dev.caset.buffalo.edu/html/batch.php), we recorded the number of "hits" (phrases sharing at least two matching lexemes) in each source–target pair (searches conducted on 2 May 2014). Hits may include exact matches of inflected forms, such as Vergil, Georgics 1.493 exesa inueniet scabra robigine pila ~ Statius, Thebaid 3.582 tunc fessa putri robigine pila (lemmata: robigo, pilum). Matches may also occur among differently inflected forms of the same lexeme, such as Vergil, Georgics 2.64 solido Paphiae de robore myrtus ~ Statius, Thebaid 4.300 hi Paphias myrtos a stirpe recuruant (lexemes: Paphius, myrtus).[10]
We used a set of search parameters that capture the most instances of interpretively significant text reuse while excluding many instances of less significant reuse. These were:
  • phrases as the search unit
  • lemma as the matching feature
  • 20 stop words, determined by frequency in the Tesserae corpus
  • scores calculated by stem
  • a maximum distance of 10, calculated by frequency
  • no score cutoff[11]
We then partitioned the results by score. Tesserae assigns each matched phrase a score (rounded to the nearest integer) according to the following formula, which reflects the observation that instances of text reuse featuring rare words in close proximity are often more interpretively significant than instances featuring common words spaced farther apart [Forstall et al. 2014] [Coffee et al. 2013].
Figure 1. 
Examples of hits of different scores are listed in Table 2.

c. Weighing of counts

We thus obtained for each pair a count of the number of hits at each score (from 2 to 11). Hits scoring 6 and lower were excluded from the analysis, since it has been shown that these are unlikely to be instances of interpretively significant text reuse [Forstall et al. 2014]. We were left with five data points for each pair, C7, C8, C9, C10, and C11 (counts of score 7, 8, 9, 10, and 11; Table 8 and 9). In order to convert these five counts into a single useful "composite count", C, we took advantage of the strongly linear relationships between counts of every score except for the rare C11 hits. Because the mean correlation was strongest between C9 and the other counts (mean R2 = 0.879; mean ρ = 0.931), the smallest amount of error was introduced by converting all counts into C9, using a combination of linear regressions and principal component analysis.
First, we used a series of linear regressions to characterize the relationship between C9 and the other four counts and obtain an initial composite count, Cregr.[12]Second, we applied principal component analysis (PCA) to the five counts, first correcting for their very different scales by dividing each count by its standard deviation, in order to obtain a second composite count, Cpca.[13] Noting the similar weights in the formulae for Cregr and Cpca, we chose the average weights for the final formula for composite counts, which we considered to be the “observed count”, Cobs:
Figure 7. 

d. Relative intensity of reuse

The resulting observed counts could not be directly compared to one another, since the total lengths of the texts were different for each source–target pair. For instance, we expected to obtain a much higher Cobs value for the pair Ovid, Metamorphoses (78098 words) – Silius Italicus, Punica (76292 words) than for the pair Horace, Ars Poetica (3090 words) – Claudian, De Bello Gildonico (3165 words), simply because there is much more space for text reuse in the longer texts. Indeed, we found that Cobs was correlated with the lengths of both source and target texts, Ws and Wt; the correlations were strongly linear when the variables were converted to a logarithmic scale (cobs, ws, and wt).
Thus, we could use a multiple regression to determine (in logarithmic scale) an expected count, cexp, for any given length of source and target text, ws and wt. We obtained the model (R2 = 0.979):[14]
Figure 9. 
We then subtracted the expected count for each source–target pair from the observed count to obtain a residual, which we considered to be a measure of the relative intensity of text reuse for each pair:
Figure 10. 
A positive value of r for a given pair indicates that the observed intensity of text reuse was higher than would be expected for an "average" pair of texts with those particular word counts — that is, for a pair of texts with no particularly strong or weak intertexual relationship. A negative value of rindicates that the observed intensity of text reuse was lower than average. The further the value deviates from zero, the stronger the evidence for an intensity of reuse above or below average. Thus, we sorted all pairs by their r values, presented in both standardized and non-standardized forms (Table 3).[15] We also presented the (non-standardized) r values graphically, partitioning the pairs by source text (Figure 11) and target text (Figure 12), and presented various subsets of the data to aid discussion (Figures 13–15, Tables 5–7).
It should be reiterated that r is not a measure of the number of phrases reused for each pair (for which Cobs is the most direct measure), but a measure of the intensity of text reuse that takes into account the lengths of the source and target texts in each pair. For instance, the very high Cobs value of 7407.3 for the pair of the longest texts in our data set, Ovid, Metamorphoses (78098 words) – Silius Italicus, Punica (76292 words), actually reflects only moderately intense text reuse (r = 0.146), whereas the very intense reuse (r = 1.280) of Vergil’s Georgics (14154 words) by Vergil’s later poem, the Aeneid (63719 words) corresponds to a lower Cobs value (1974.8) because the texts are shorter.

e. Centrality

For each of our 24 chosen texts, we determined the mean value of r for all pairs involving that text (23 pairs each time), and sorted the texts by the results (Table 4). We considered this to be a measure of the "centrality" of each of our chosen texts within the 24–text set: that is, how often each text reuses earlier texts and is reused by later texts. A text strongly influenced by its predecessors and influential to its successors would have a higher mean r than a text more peripheral to the literary tradition of Latin hexameter poetry.

3. RESULTS AND DISCUSSION

We have kept two objectives in mind in interpreting our data set. First, we attempt to test whether the results of the automated search and statistical analysis match the conclusions reached by traditional scholarship. Second, we endeavor to identify unexpected results that suggest avenues for future research. We achieve those two objectives when interpreting both general (sections 3.a-b) and specific trends (section 3.c).

a. Statistical outliers and centrality

Three pairs with standardized residuals near or above |3| may be considered statistical outliers (GeorgAen, standardized r = 4.571; MetMos, 3.830; ArsGild, –2.977). These results reflect several phenomena that we will discuss: the influence of author on text reuse (GeorgAen, section 3.b), the influence of genre (ArsGild, 3.b), and the importance of Ovid (among others) to late antique hexameter (MetMos, 3.c.iv). For a further 11 pairs, standardized residuals near or above |2| indicate intensity of text reuse markedly above or below average; these results also reflect phenomena that we will discuss.[16] These standard statistical thresholds should not be relied upon naively, however: for instance, several pairs for which we would expect a strong intertextual engagement (such as texts written by the same authors) had standardized r values well below 2.
The centrality scores conformed to expectations (Table 4). The high centrality of the Aeneid (0.133) reflects the importance of Vergil’s works to the subsequent hexameter tradition, while the high centrality of the Ilias Latina (0.186) reflects multiple reuse facilitated by its intense reuse of the Aeneid (see section 3.c.i). The high centrality of the Georgics (0.279) stems from a combination of these factors. All four of Claudian’s works had positive centrality. This reflects not only Claudian’s extensive reuse of his predecessors, but also the influence of authorship on text reuse: each of Claudian’s works had high r values when paired with the other three works, thus increasing their centrality. The low centrality of the works of Horace, Persius, Juvenal, and Lucretius reflects the influence of genre in our data set comprising mainly epic/panegyric texts. Perhaps the most unexpected result is the high centrality of the Achilleid (0.117), which reflects both intense reuse of earlier epic sources and intense reuse by later epic targets. Because the Achilleid is a very short text, certain considerations must be kept in mind (see section 3.c.i).

b. General trends

Unsurprisingly, the most important influence on text reuse intensity was authorship. In all 13 cases where a pair of texts was written by the same author, the reuse intensity was higher than average (r > 0.000), markedly so in 5 of the cases (standardized r > 2.000); see Figure 13 and Table 5. Vergil showed the highest intensity of text reuse within his own poems, followed by Claudian, while Horace and Statius reused their own poems with less intensity. Though drawing on a very different data set (a relatively small corpus of Latin hexameter poems), the results are nevertheless broadly comparable to Jockers’ study of the author signal in a corpus of 3500 nineteenth-century novels written in English. Jockers observes that of five "signals" (author, decade, genre, gender, and text), the author signal is the strongest.[17]
A secondary influence on text reuse intensity was genre. Although categorizing Latin poetry by genre is difficult, we may obtain a rough idea of the influence of genre by partitioning the texts of our data set into three genres: didactic, epic/panegyric, and satiric (Figure 14).[18] Within the small didactic and satiric genres, reuse intensity was higher than average for 5 of 6 pairs (r > 0.000; the exception, HSat – JSat, was slight: r = −0.007). Within the much larger (and more diverse) epic/panegyric genre, reuse intensity was higher than average in 66 of 78 pairs; the 12 remaining pairs had only slightly lower than average reuse intensity (standardized r ≥ −0.446). In contrast, pairs comprising texts from different genres tended to display lower than average reuse intensity. The trend was clearest for pairs composed of one epic/panegyric and one satiric text: 37 of 39 pairs had lower than average reuse intensity.[19] The results conform to the expectations of traditional reading, as epic and satire are the most distant hexameter genres from one another in style and subject matter. Genre is also perhaps the best explanation for the trends seen in the "centrality" measure (Table 4). Since 13 of 24 texts in our data set belong to the epic/panegyric genre, we would expect each of them to be more central than texts belonging to smaller genres. This is true in most cases; the most notable exception is the Georgics, which had the highest centrality score by far, despite belonging to the didactic genre. We discuss this exceptional text in section 3.c.i.
Time period appeared to have no influence on text reuse intensity. This is not surprising, since the technical and aesthetic constraints of hexameter poetry discouraged changes in diction or syntax over time. However, it is possible that a future study which controls for much more salient influences such as authorship and genre may discover a subtle influence of time period.

c. Specific observations

The 276 pairs in our data set represent a generically and chronologically diverse collection of texts. Different scholars will accordingly highlight various aspects of the data. We only offer a handful of specific observations here. As with the general trends we observed, these specific results both confirmed that our analysis falls in line with the results of traditional scholarship and identified several possible avenues for future inquiry. For instance, Virgil’s Aeneid predictably emerged as a major influence on subsequent poetry of all periods. Lucretius’ De Natura Rerum was not a prominent verbal resource for later authors. The four Flavian epics were closely related, and late antique poets reused material from previous works in expected ways. The congruence of these results with traditional scholarship supports our contention that several unexpected results are indicators of potential for fruitful further research. For instance, Virgil’s Georgics and the anonymous Ilias Latina scored high in reuse intensity in almost every case. This is probably an indication of frequent multiple allusions to both these texts and the more prominent Aeneid and Metamorphoses (section 3.c.i). The relationship between the Flavian epics and the Aeneid appears to be more "creative" or "original" than often allowed, although these terms must be used carefully (see 3.c.ii). Horace’s Ars Poetica seems to have an unexpected influence on Manilius’ Astronomicon, suggesting that didactic sensibility may cut across genre (see 3.c.iii). Finally, Ausonius’ Mosella, usually considered primarily "Vergilian" in nature, also shows close links with Ovid’s Metamorphoses (3.c.iv).

i. Vergil’s Georgics and the Ilias Latina

The influence of Vergil’s Aeneid on the subsequent tradition of Latin hexameter is well established and reflected in our results. The work had a high centrality score (0.133) and higher than average reuse intensity (r > 0.000) when paired with 13 of 18 subsequent target texts (the exceptions are BC and the non-epic texts Ars, PSat, JSat, and HE); see Tables 4 and 6 and Figure 11. However, the results for Vergil’s early work, the Georgics, are even more exceptional. Its centrality score was more than twice as high (0.279) and it had higher than average reuse intensity (r > 0.000) when paired with 16 of 20 subsequent target texts (the exceptions are the non-epic texts Ep, Ars, PSat, and JSat). These results may seem surprising at first. Although the Georgics is an important text, few would argue that its influence on subsequent Latin literature eclipses that of the Aeneid. But two factors must be kept in mind. First, recall that r is not a measure of the number of phrases reused for each pair (for which Cobs is the most direct measure), but a measure of the intensity of text reuse that takes into account the lengths of the texts in each pair. Because the Aeneid is much longer than the Georgics (63719 vs 14154 words), it requires values of Cobs over 7 times higher, and thus the reuse of many more phrases, in order to achieve the same residual when paired with any subsequent target text. Subsequent target texts use many more phrases from the Aeneid than from the Georgics in total,[20] and the influence of the Aeneid on subsequent literature is therefore more obvious to the reader. Yet the intensity of the reuse is greater for the shorter Georgics.
The second factor arises from Vergil’s extensive reuse in the Aeneid of his own phrases from the Georgics, which resulted in the highest r value in our data set (1.280), one of three statistical outliers (standardized r = 4.571). Because Vergil’s two texts share many phrases, subsequent target texts that reuse phrases from one Vergilian text will often automatically reuse the same phrase from the other Vergilian text. In practice, subsequent epic poems that reuse phrases from the epic Aeneid will often automatically reuse the same phrase from the Georgics. A similar phenomenon explains the unexpected results for the Ilias Latina. Although no scholar would argue that this minor poem, a rough compression and translation of the Iliad, exerted any discernable influence on Latin literature in antiquity,[21] it had a higher centrality score than the Aeneid (0.186) and higher than average reuse intensity (r > 0.000) when paired with every subsequent target text (Tables 4 and 6 and Figure 11). However, the Ilias Latina also had markedly higher than average reuse intensity (standardized r > 2.000) when paired with both the Aeneid and Ovid’s Metamorphoses, two foundational texts for later Latin literature.[22] This suggests that when a subsequent target text reuses phrases from either the Aeneid or the Metamorphoses, it will often automatically reuse the same phrase from the Ilias Latina and thereby increase the r value when paired with that poem.
The high scores for both the Georgics and Ilias Latina demonstrate that allusion in Latin literature is not always a case of a target text reusing a phrase from a single, specific source text. On the contrary, an allusion to, say, the Aeneid often necessarily entails an allusion to the Georgics, the Ilias Latina, or some other text(s). While scholars routinely privilege one source text at the expense of the others for the sake of interpretation, the automatic searches of Tesserae do not. This egalitarian interpretive practice is not very suitable in the case of the Ilias Latina, a minor text rightly subordinated to the sources it reuses, but it is more suitable in the case of the Georgics, where readers will more often hit upon compelling interpretations by treating the Georgics as a source text on par with the Aeneid.[23] Tesserae encourages this kind of interpretation not only by presenting all texts as equal in value, but also by offering the option to perform multi-text searches (http://tesserae.caset.buffalo.edu/multi-text.php), where matches between a source–target pair are presented alongside every other instance of the matching phrase in a user-selected set of texts.

ii. Post-Vergilian classical epic

Scholarly interest in post-Vergilian classical epic (the Metamorphoses, Bellum Civile, Argonautica, Thebaid, Achilleid, and Punica) has roughly tracked the chronology of the epics themselves, with attention paid first to the Metamorphoses and last to the Punica. Similarly, the assumption has often been made that the earlier epics (Metamorphoses and Bellum Civile) responded to Vergil’s influence in more creative and original ways, while the four later epics of the Flavian period tended to imitate Vergilian epic less creatively.[24] To compare this assumption to the results of our study, we must bear in mind the nature of the text reuse that Tesserae can discover. At its current stage of development, Tesserae identifies only matching phrases with exact repetition of two or more lexemes. It cannot detect allusions signaled by similarity of action, character, or theme, or text reuse involving single significant words or verbal variations. That is, Tesserae preferentially detects exactly the sort of allusions that may be classified as less "creative". Thus a high residual indicates not only higher than expected text reuse, but also potentially a less "creative" allusive relationship.
Bearing this in mind, the results do not fully support the assumption of declining creativity over time (Figure 15 and Table 7). In contrast, although the intensity of text reuse of both the Georgics and Aeneid by the Argonautica, Thebaid, and Achilleid was higher than average (0.160 ≤ r ≥ 0.299), it was not as high as the intensity of reuse of any of Vergil’s three works by the Metamorphoses (0.323 ≤ r ≥ 0.560). The intensity of reuse of Vergil by the Bellum Civile was even lower: in fact, the intensity of reuse of the Aeneid was slightly lower than average (r = −0.026).[25] Thus, it would seem that the intertextual engagement with Vergil’s texts by Lucan, Valerius Flaccus, and Statius are either less intense or more "creative" (or both) than often assumed.
The notable exception is the Punica of Silius Italicus, which had much higher than average intensity of text reuse when paired with the Georgics (r = 0.433) and Aeneid (r = 0.540). This is consistent with the assumption of an uncreative intertextual relationship, and inconsistent with recent claims about the Punica’s originality.[26] It must be acknowledged, however, that "originality" and "creativity" are subjective concepts, which are not directly measured by r values. A high r value for a given pair indicates only that the number of matching phrases of two or more lexemes was greater than expected for an "average" pair of texts with the same word counts. It does not indicate, for instance, a paucity of other kinds of subtler intertextuality (text reuse with verbal variation, or similarities of action, theme, or character). Nor does it take into account the context into which the lexemes are redeployed: a poet may, for instance quote a predecessor’s words exactly, but in a completely different and original context.
Other observations may be made about the results for the four Flavian epics. The high r values for the epics when paired with the Georgics (0.160 ≤ r ≥ 0.433) may be influenced by factors discussed in section 3.c.i, but scholars have begun to interpret the relationship between these texts more aggressively (Pagán 2015), and our results support this line of inquiry. The Metamorphoses and Bellum Civile have often been interpreted as important texts for the Flavian epics; however, although the intensity of text reuse for the eight relevant pairs was usually higher than average (r ≥ −0.075), it was usually only moderately so, approximately on par with the intensity of reuse for the epics when paired with the Eclogues, a text rarely argued to be important to Flavian epic. Again, this does not argue against a strong intertextual engagement between the Metamorphoses, Bellum Civile, and Flavian epics; it may instead suggest that future investigations should focus on allusions not signalled by the obvious text reuse that Tesserae discovers.
The intertextual relationship between the four Flavian epics has been the subject of recent study, and this line of inquiry is supported by our results. The intensity of the Thebaid’s reuse of the Argonautica was slightly higher than average, on par with the Thebaid’s reuse of the Metamorphoses (r = 0.064, 0.037). The intensity of the Achilleid’s reuse of the Argonautica was much higher than average, on par with the Achilleid’s reuse of the Aeneid (r = 0.279, 0.289).While the intertextual relationship between the Thebaid and Argonautica has been well studied, the relationship between the Achilleid and Argonautica has not;[27] future work in this vein could be productive. Unsurprisingly, the intensity of reuse of Statius’ Thebaid by Statius’ later Achilleid was higher than average (r = 0.141), but it was lower than 11 of the 12 remaining intra-author pairs (Figure 13 and Table 5). This low reuse cannot be explained purely by the divergent subject matter and style of Statius’ two epics: Vergil’s Eclogues and Aeneid are at least as divergent, but had a higher r value (0.224). Finally, the r value for the pair AchilleidPunica was very high (0.410).[28] This was unexpected. Research on the intertextual relationship between Statius’ and Silius’ works has focused on the pair ThebaidPunica,[29] but these results suggest more attention should be paid to the Achilleid. In all discussion of the Achilleid, however, we should keep in mind that it is much shorter than the other three Flavian epics; therefore, the considerations that applied to the Georgics in section 3.c.i apply here.

iii. Didactic and satiric hexameter

Hardie’s study of the reception of Lucretius makes a strong and well-received case for the fundamental contribution of the De Rerum Natura to succeeding poetry from the Augustan poets through Milton’s Paradise Lost [Hardie 2009]. No reader would dispute the conceptual and formal importance of the DRN to the Latin hexameter tradition. Features of later hexameter poetry such as sententiae, multiple explanations, and similes from the natural world all bear the marks of the Epicurean poet’s mode of argumentation. Yet the vocabulary of the DRN was not mined as extensively as the other foundational works of Republican and Augustan poetry, as can be seen from our results (centrality = −0.151, r < 0.000 when paired with 21 of 23 succeeding target texts; Figure 11). The only positive r values resulted from pairings with other didactic works: Vergil’s Georgics (r = 0.230) and Manilius’ Astronomica (r = 0.023). While these results are consistent with the observed influence of genre on text reuse (section 3.b), the low r values overall demonstrate the difference between the importance of Lucretius’ poem as a conceptual resource and its importance as a verbal resource.
Volk’s study of the Astronomica makes a series of valuable observations about Manilius’ thematic adaptations of Lucretius, Vergil, and Ovid [Volk 2009]. Those thematic adaptations were accompanied by verbal reuse only for Vergil in our results. Vergil’s Georgics yielded the highest reuse intensity (r = 0.342), followed by the Eclogues (r = 0.307). Unexpectedly, Horace’s Ars Poetica had the next highest r value (0.213). As the Ars is one of the shortest poems in our data set, the considerations that applied to the Georgics in section 3.c.i apply here. Yet there may be hitherto unexplored verbal connections between the poem on composing poetry and the poem of the stars, likely in the addresses of the didactic narrator. The intensity of reuse of the DRN was higher than average, but only negligibly so (r = 0.023). The intensity of text reuse of the Astronomica by later texts was low, suggesting a limited influence on the language of subsequent classical hexameter tradition.
The inclusion of the Satires of Horace, Persius, and Juvenal (HSat, PSat, JSat) in this study permits us to begin investigation of the influence of genre on text reuse in Latin hexameter. As mentioned above (section 3.b), the author signal is a stronger determinant than the genre signal for intensity of text reuse, as evidenced by higher r values for pairs of texts written by Horace than inter-author pairs within the satiric genre.[30] But the importance of genre was especially marked when pairing epic/panegyric with satiric texts, where 37 of 39 pairs had lower than average reuse intensity (r < 0.000), including the lowest r values in our data set (Figure 14).[31] These results indicate a strong separation between the genres, related to satire’s pedestrian vocabulary and everyday concerns, which contrast with the more elevated style and subject matter of epic.

iv. Late antiquity

The tremendous influence of Vergil and Ovid on the hexameter poems of late antiquity has been well recognized in prior scholarship, but has been typically studied from the perspective of theme, character, and subject. The present study permits some initial quantification of the intensity of text reuse between these poems and those occurring earlier in the hexameter tradition.
Prior scholarship has identified Ausonius’ Mosella as primarily Vergilian in character, with several secondary influences, but has not heretofore been able to quantify the nature of Ausonius’ reuse of his predecessors’ texts.[32] In our study, the intensity of text reuse of Ovid’s Metamorphoses by the Mosella was markedly higher than average (standardized r > 2.000). This pairing had the highest r value of any two independently authored texts (r = 1.073), and second only to Vergil’s reuse of the Georgics in the Aeneid (r = 1.280). The intensity of reuse of Vergil’s works was decidedly lower (Georgics, r = 0.260; Aeneid, r = 0.115). The intensity of reuse of Statius’ Achilleid and Silius Italicus’ Punica was slightly above average (r = 0.104 and 0.028), but lower than that of Manilius’ Astronomica and the Ilias Latina (r = 0.130 and 0.120; for the latter, see section 3.c.i). Intensity of reuse was lower than average (r < 0.000) for Lucretius’ De Rerum Natura, Lucan’s Bellum Civile, Valerius Flaccus’ Argonautica, and Statius’ Thebaid. The centos entirely composed of phrases adapted from Vergil’s works that appear in this period represent a new level of engagement with the foundational texts of the genre [McGill 2005]. Ausonius’ Cento Nuptialis, the best known of the centos, is available on Tesserae, but was excluded in this study, since its artificially high reuse rates of Vergil’s works would have produced extreme outliers that would have distorted our results.
As observed above (section 3.b), the works of Claudian are evidence for the strength of the author signal. Four of the top fifteen r values in our data set were derived from pairing works of Claudian (HonStil, HonGild, GildStil, and RaptHon; 0.461 ≤ r ≥ 0.716). The lower position of the De Raptu Proserpinae among the pairings of Claudian’s works (RaptHon, RaptGild, RaptStil; 0.243 ≤ r ≥ 0.461) may suggest that Claudian’s self-reuse is strongest among works in a similar genre (panegyric rather than mythological epic). We are hesitant to draw firm conclusions, however, about the relative importance of the author and genre signals with so few data. Claudian’s rates of reuse of his Augustan predecessors present a similar story to that told in the scholarly literature [Ware 2012, 9-10]. For instance, Vergil’s Georgics (r = 0.538) and Aeneid (r = 0.326) had high reuse intensity when paired with Claudian’s mythological De Raptu Proserpinae. The intensity of reuse of Statius’ Achilleid was also high (r = 0.426), which accords with the importance of Statius as an intermediary between the Augustans and the poets of late antiquity. As Kaufmann observes, "Claudian, possibly inspired by Ausonius, [was] the trendsetter for the increased interest in Statius’ poetry by the later poets"  [Kaufmann 2015]. An unexpected but plausible result is the importance of Lucan’s Bellum Civile to Claudian’s historical panegyrics, Gild (r = 0.351) and Hon (r = 0.278).
We also included Juvencus’ Historia Evangelica, a fourth-century Christian epic, and Corippus’ Johannis, a sixth-century historical epic, in the data set. Both the Johannis’ high rates of reuse of Vergil and Claudian and the HE’s low rates of reuse of classical pagan poetry (with the exception of the Georgics and Ilias Latina) conform to the expectations set by the scholarly literature.[33]

4. CONCLUSIONS

We chose to begin by studying a selected corpus of Latin hexameter poems because relationships between works in this "super-genre" have been the most closely studied of all intertextual relationships in ancient literature. We are able to compare the information about the relative rates of reuse of texts in Table 3 to a long tradition of qualitative discussion of allusion by Latinists. We provisionally conclude that a majority of the results conform to the statements typically made by poetry scholars about the significance of various intertextual relationships in the Latin hexameter tradition. For instance, the author signal is one of the strongest determinants of intensity of text reuse, the works of Ovid and Vergil are the most important verbal resources for the later works of the tradition, and satiric hexameter is strongly separated from the other hexameter genres in terms of reuse. If it is accepted that the high level of correlation between our quantified results and the scholarly tradition’s qualitative assessments provides a strong vote of confidence for our methodology, then we can begin to explore the significance of unexpected findings. These include (a) the importance of Vergil’s Georgics to the later tradition, (b) the indications of multiple reuse visible in the Ilias Latina, (c) the relatively low reuse of Vergil by Lucan, Valerius, and Statius, and (d) the intense reuse of Ovid’s Metamorphoses by Ausonius’ Mosella.
This is a first step in algorithmic criticism of the hexameter super-genre [Ramsay 2011]. As observed in the Introduction, Tesserae has some limitations which reflect its current state of development, and others which reflect the nature of Latin poetry. In this initial study, we confirmed the value of the lexeme-matching approach by comparing it to the traditional critical narrative of relationships among Latin hexameter poems. Our goal is to model a system of relationships between texts that can frame critics’ discussions of the role of individual poems within the tradition. As Drucker observes, "on the surface, a model seems static. In reality it is, like any 'form,' a provocation for a reading, an intervention, an interpretive act"  [Drucker 2009, 16]. In Drucker’s terms, Tesserae modeling is a dynamic rather than static approach to textual analysis. New data sets can easily be constructed, whether by using different Tesserae parameters or changing the texts in the group under analysis. These future analyses will produce new and different perceptions of the system of relationships among Latin literary texts in other genres, or between other genres and the hexameter super-genre.

Tables and Figures

Text Abbreviation (name of work) Date (approximate) Length (words)
Lucretius, De Rerum Natura DRN before 55 BCE 49099
Vergil, Eclogues Ecl 42–39 BCE 5617
Horace, Satires HSat 40–30 BCE 14215
Vergil, Georgics Georg 36–29 BCE 14154
Horace, Epistles Ep 23–20 BCE 9906
Vergil, Aeneid Aen 29–19 BCE 63719
Horace, Ars Poetica Ars 14 BCE 3090
Ovid, Metamorphoses Met 2–8 CE 78098
Manilius, Astronomica Astr after 9 CE 27353
Persius, Satires PSat before 62 CE 4457
Lucan, Bellum CivileM BC 64–65 CE 51065
[Italicus], Ilias Latina Ilias 60–70 CE 6597
Valerius Flaccus, Argonautica Arg before early 90s CE 37250
Statius, Thebaid Theb 92 CE 62504
Statius, Achilleid Ach 95 CE 7204
Silius Italicus, Punica Pun before 96 CE 76292
Juvenal, Satires JSat after 96 CE 24884
Juvencus, Historia Evangelica He 330 CE 19854
Ausonius, Mosella Mos 370 CE 2957
Claudian, De Raptu Proserpinae Rapt 395–397 CE 6991
Claudian, De Quarto Consulatu Honorii Augusti Hon 397 CE 3965
Claudian, De Bello Gildonico Gild 398 CE 3165
Claudian, De Consolatu Stilichonis Stil 399–400 CE 7583
Corippus, Johannis Joh 6th c. CE 29046
Table 1. 
Score 11
Pun 13.752 miscuerint Italis Piraeo litore leges
Met 6.444 Cecropios intrat Piraeaque litora tangit
Ilias 401 instat et exstructos morientum calcat aceruos
Met 5.85 sternit et exstructos morientum calcat acervos
Score 10
Theb 10.228 cum fetura gregem pecoroso vere novavit
Ecl 7.35 si fetura gregem suppleverit, aureus esto
Astr 2.807 per latera atque imum templi summumque cacumen
Aen 6.678 dehinc summa cacumina linquunt
Score 9
Astr 1.753 nec mihi celanda est famae vulgata vetustas
Aen 12.608 Hinc totam infelix volgatur fama per urbem
JSat 10.99 an Fidenarum Gabiorumque esse potestas
HEp 1.11.7 Gabiis desertior atque / Fidenis vicus
Score 8
Theb 7.262 arma patris pinuque iubas imitatur equinas, / terribilis silvis
Ecl 2.31 Mecum una in silvis imitabere Pana canendo
Astr 4.897 pars sua perspicimus genitique accedimus astris
Aen 9.641 sic itur ad astra, / dis genite et geniture deos
Score 7
Theb 7.447 ipsa loco mirum natura favebat
Ecl 3.68 ipse locum, aëriae quo congessere palumbes
Astr 4.96 quin etiam infelix virtus et noxia felix
Aen 9.799 Quin etiam bis tum medios invaserat hostis
Table 2. 
Randomly selected examples of hits from Tesserae searches scoring 11, 10, 9, 8, and 7.
Source Target r Standardized r
Georg Aen 1.280 4.571
Met Mos 1.073 3.830
Met Ilias 0.719 2.565
Hon Stil 0.716 2.555
Ilias Joh 0.663 2.368
Hon Gild 0.634 2.264
Ecl Georg 0.603 2.153
Aen Ilias 0.594 2.119
Gild Stil 0.575 2.054
Georg Met 0.560 1.999
Aen Pun 0.540 1.928
Georg Rapt 0.538 1.921
Rapt Hon 0.461 1.644
Ilias Gild 0.457 1.631
Georg Pun 0.433 1.546
Ilias Pun 0.433 1.545
Gild Joh 0.427 1.525
Ach Rapt 0.426 1.520
Ach Pun 0.410 1.462
Rapt Gild 0.404 1.442
Ilias Ach 0.396 1.414
Mos Hon 0.395 1.411
Ilias Arg 0.389 1.387
Ach Joh 0.375 1.337
Hon Joh 0.372 1.327
Georg Joh 0.355 1.266
Ep Ars 0.354 1.262
Georg BC 0.351 1.253
BC Gild 0.351 1.252
Aen Met 0.350 1.249
Georg Astr 0.342 1.221
Ach Stil 0.331 1.183
Aen Rapt 0.326 1.162
Rapt Stil 0.324 1.157
Ecl Met 0.323 1.151
Georg Ilias 0.310 1.107
Ecl Astr 0.307 1.096
Rapt Joh 0.302 1.079
Aen Theb 0.299 1.067
Georg Arg 0.297 1.061
Aen Ach 0.289 1.033
Arg Ach 0.279 0.996
BC Hon 0.278 0.992
Aen Joh 0.269 0.961
Georg Gild 0.268 0.957
HE Joh 0.267 0.951
Ach Gild 0.263 0.939
Georg Mos 0.260 0.928
HSat Ep 0.259 0.925
Aen Arg 0.255 0.910
BC Stil 0.253 0.903
Ilias Theb 0.252 0.899
BC Rapt 0.250 0.893
Mos Stil 0.247 0.883
Mos Joh 0.243 0.866
Ach Hon 0.238 0.851
Met BC 0.238 0.850
Georg Hon 0.232 0.829
DRN Georg 0.230 0.823
Ars Stil 0.228 0.813
Ecl Aen 0.224 0.800
Ecl Ilias 0.224 0.799
Ilias HE 0.223 0.795
Ars Astr 0.213 0.762
HSat PSat 0.210 0.750
Stil Joh 0.199 0.711
Georg Theb 0.186 0.664
Georg HE 0.172 0.614
Georg Ach 0.160 0.570
Ilias Stil 0.157 0.560
Mos Rapt 0.153 0.546
Ilias Rapt 0.152 0.543
Met Pun 0.146 0.520
Theb Ach 0.141 0.503
PSat JSat 0.137 0.490
Georg Stil 0.132 0.472
BC Joh 0.132 0.471
Astr Mos 0.130 0.465
Theb Rapt 0.128 0.457
Pun Rapt 0.128 0.457
BC Pun 0.126 0.450
Astr Ilias 0.125 0.446
Ilias Mos 0.120 0.428
Aen Mos 0.115 0.409
Ach Mos 0.104 0.373
Astr Joh 0.101 0.361
BC Ach 0.097 0.348
Arg Gild 0.097 0.346
Ecl Stil 0.094 0.335
Ecl Pun 0.093 0.332
Aen Gild 0.092 0.328
Met Rapt 0.089 0.319
Ars JSat 0.078 0.278
Met Ach 0.077 0.276
Arg Pun 0.076 0.272
HE Gild 0.075 0.267
Arg Rapt 0.067 0.239
Aen Hon 0.064 0.229
Arg Theb 0.064 0.229
Pun Hon 0.060 0.214
Theb Pun 0.057 0.204
JSat Hon 0.053 0.188
Theb Hon 0.052 0.185
Pun Joh 0.051 0.182
Astr BC 0.048 0.171
Astr Ach 0.047 0.168
Ecl Ach 0.047 0.167
Ilias JSat 0.045 0.160
Mos Gild 0.042 0.150
HSat Ars 0.041 0.146
HSat Georg 0.037 0.133
Met Theb 0.037 0.131
Ilias Hon 0.036 0.130
Astr Hon 0.036 0.130
BC Arg 0.035 0.125
Aen Stil 0.030 0.108
BC Ilias 0.028 0.100
Pun Mos 0.028 0.099
Arg Hon 0.024 0.087
DRN Astr 0.023 0.082
Pun Gild 0.018 0.065
Met Stil 0.017 0.060
Ars HE 0.013 0.047
Aen Astr 0.011 0.039
Ars PSat 0.008 0.028
Ep JSat 0.003 0.010
Ecl Arg -0.003 -0.012
Met Arg -0.006 -0.020
Theb Stil -0.006 -0.022
Astr Stil -0.007 -0.026
HSat JSat -0.007 -0.026
Ecl Rapt -0.009 -0.032
Georg JSat -0.009 -0.033
HE Rapt -0.010 -0.036
Astr Pun -0.013 -0.046
DRN Aen -0.015 -0.054
HE Stil -0.016 -0.058
Astr Rapt -0.016 -0.058
DRN Ilias -0.017 -0.062
Ecl JSat -0.021 -0.076
Met Hon -0.022 -0.077
Aen BC -0.026 -0.091
Arg Joh -0.030 -0.106
Arg Stil -0.039 -0.138
Ep PSat -0.040 -0.141
DRN Hon -0.042 -0.149
Georg Ep -0.045 -0.162
Aen HE -0.047 -0.169
DRN Ars -0.052 -0.184
Met Gild -0.055 -0.197
Ecl Mos -0.058 -0.206
Pun Stil -0.059 -0.212
Met Astr -0.064 -0.228
Ecl HSat -0.066 -0.237
Ach JSat -0.068 -0.242
BC Theb -0.075 -0.268
Ach HE -0.076 -0.273
Astr Gild -0.077 -0.276
HE Mos -0.079 -0.283
JSat Gild -0.081 -0.288
Theb Gild -0.081 -0.289
Met Joh -0.085 -0.302
Ecl HE -0.089 -0.318
Ecl BC -0.089 -0.319
Astr HE -0.090 -0.321
Ep Stil -0.090 -0.323
DRN Ach -0.091 -0.324
DRN Pun -0.092 -0.329
JSat Mos -0.094 -0.334
Ecl Joh -0.098 -0.351
Ars BC -0.100 -0.355
DRN Joh -0.101 -0.361
HSat Ach -0.102 -0.364
JSat Joh -0.104 -0.372
DRN Rapt -0.111 -0.394
DRN Mos -0.111 -0.397
HE Hon -0.112 -0.400
Ars Met -0.112 -0.401
JSat Rapt -0.113 -0.405
Ep Astr -0.114 -0.406
Georg Ars -0.114 -0.408
Astr Arg -0.114 -0.409
JSat Stil -0.117 -0.418
Ep Hon -0.117 -0.418
Ep Mos -0.121 -0.433
Theb Joh -0.125 -0.446
Theb Mos -0.128 -0.459
Ars Mos -0.131 -0.467
Ep Rapt -0.133 -0.476
DRN Ecl -0.134 -0.480
Arg HE -0.137 -0.490
Astr JSat -0.139 -0.496
DRN Ep -0.139 -0.497
PSat Stil -0.139 -0.498
BC Mos -0.142 -0.506
Ecl Theb -0.145 -0.518
Pun HE -0.154 -0.550
DRN Met -0.164 -0.585
Georg PSat -0.164 -0.587
DRN Stil -0.170 -0.606
Ars Ilias -0.171 -0.609
Ecl Ep -0.171 -0.610
DRN HSat -0.183 -0.654
PSat Mos -0.185 -0.661
Ars Ach -0.187 -0.668
Ep Ach -0.188 -0.670
Astr Theb -0.189 -0.673
HSat Ilias -0.195 -0.697
Ars Pun -0.195 -0.697
BC JSat -0.203 -0.724
HSat Pun -0.205 -0.731
PSat Arg -0.211 -0.754
BC HE -0.215 -0.768
Ep Aen -0.216 -0.772
DRN HE -0.221 -0.789
PSat Pun -0.230 -0.823
HSat Astr -0.236 -0.842
Met JSat -0.236 -0.843
HSat HE -0.242 -0.866
HSat Gild -0.243 -0.866
Aen JSat -0.243 -0.867
HSat Aen -0.243 -0.869
HSat Stil -0.244 -0.870
Ep Ilias -0.245 -0.873
Met HE -0.246 -0.877
HSat Mos -0.253 -0.903
Ep Gild -0.253 -0.903
Ep Met -0.261 -0.931
Ars Rapt -0.272 -0.971
JSat HE -0.273 -0.973
PSat Ach -0.273 -0.976
Ep Arg -0.279 -0.995
DRN Arg -0.283 -1.009
Ep BC -0.288 -1.028
Arg Mos -0.290 -1.035
Theb HE -0.293 -1.045
DRN BC -0.297 -1.059
Pun JSat -0.298 -1.062
PSat BC -0.300 -1.071
Ep Joh -0.301 -1.075
Arg JSat -0.303 -1.083
Ars Arg -0.304 -1.084
PSat Hon -0.315 -1.126
Ecl PSat -0.316 -1.127
DRN PSat -0.316 -1.128
HSat Joh -0.322 -1.148
HSat Met -0.326 -1.163
HSat BC -0.326 -1.165
DRN JSat -0.330 -1.179
Ep HE -0.336 -1.198
Ep Pun -0.338 -1.208
Ecl Hon -0.341 -1.219
Ars Joh -0.348 -1.242
Ars Hon -0.351 -1.254
PSat Theb -0.354 -1.264
Aen Ars -0.356 -1.269
DRN Theb -0.363 -1.296
Ecl Ars -0.370 -1.320
HSat Hon -0.376 -1.342
Met PSat -0.379 -1.353
HSat Theb -0.387 -1.381
Ars Theb -0.390 -1.393
HSat Arg -0.404 -1.442
PSat Ilias -0.406 -1.448
Ecl Gild -0.422 -1.507
Theb JSat -0.434 -1.548
PSat Gild -0.444 -1.584
Ep Theb -0.451 -1.609
PSat Joh -0.453 -1.617
PSat HE -0.454 -1.621
Astr PSat -0.468 -1.669
DRN Gild -0.484 -1.726
HSat Rapt -0.485 -1.731
Aen PSat -0.537 -1.917
PSat Rapt -0.579 -2.065
Ars Gild -0.834 -2.977
Table 3. 
Intensity of text reuse for 276 pairs of hexameter texts from the 1st century BCE to the 6th century CE, determined by comparing composite counts of high scoring results in Tesserae searches with expected counts based on text lengths. Reuse intensity is presented as both non-standardized and standardized residuals.
Text Mean r
Georg 0.279
Ilias 0.186
Aen 0.133
Ach 0.117
Stil 0.105
Rapt 0.088
Hon 0.086
Joh 0.078
Met 0.073
Mos 0.057
Pun 0.044
Gild 0.032
BC 0.006
Astr -0.006
Ecl -0.018
Arg -0.036
Theb -0.096
HE -0.102
JSat -0.120
Ars -0.146
DRN -0.151
Ep -0.153
HSat -0.187
PSat -0.270
Table 4. 
Centrality scores for 24 hexameter texts from the 1st century BCE to the 6th century CE, determined by calculating for each text the mean text reuse intensity for all 23 pairs involving that text.
Horace Vergil Statius Claudian
Source Target r Source Target r Source Target r Source Target r
Ep Ars 0.354 Georg Aen 1.280 Theb Ach 0.141 Hon Stil 0.716
HSat Ep 0.259 Ecl Georg 0.603       Hon Gild 0.634
HSat Ars 0.041 Ecl Aen 0.224       Gild Stil 0.575
            Rapt Hon 0.461
            Rapt Gild 0.404
            Rapt Stil 0.324
Table 5. 
Intensity of text reuse for pairs of hexameter texts written by the same author.
Georg Aen Ilias
Target r Target r Target r
Aen 1.280 Ilias 0.594 Joh 0.663
Met 0.560 Pun 0.540 Gild 0.457
Rapt 0.538 Met 0.350 Pun 0.433
Pun 0.433 Rapt 0.326 Ach 0.396
Joh 0.355 Theb 0.299 Arg 0.389
BC 0.351 Ach 0.289 Theb 0.252
Astr 0.342 Joh 0.269 HE 0.223
Ilias 0.310 Arg 0.255 Stil 0.157
Arg 0.297 Mos 0.115 Rapt 0.152
Gild 0.268 Gild 0.092 Mos 0.120
Mos 0.260 Hon 0.064 JSat 0.045
Hon 0.232 Stil 0.030 Hon 0.036
Theb 0.186 Astr 0.011
HE 0.172 BC -0.026
Ach 0.160 HE -0.047
Stil 0.132 JSat -0.243
JSat -0.009 Ars -0.356
Ep -0.045 PSat -0.537
Ars -0.114
PSat -0.164
Table 6. 
Intensity of text reuse for pairs of hexameter texts with Vergil’s Georgics, Vergil’s Aeneid, or the Ilias Latina as source text.
Met BC Arg Theb Ach Pun
Source r Source r Source r Source r Source r Source r
Georg 0.560 Georg 0.351 Georg 0.297 Aen 0.299 Aen 0.289 Aen 0.540
Aen 0.350 Met 0.238 Aen 0.255 Georg 0.186 Arg 0.279 Georg 0.433
Ecl 0.323 Aen -0.026 BC 0.035 Arg 0.064 Georg 0.160 Ach 0.410
Ars -0.112 Ecl -0.089 Ecl -0.003 Met 0.037 Theb 0.141 Met 0.146
DRN -0.164 Ars -0.100 Met -0.006 BC -0.075 BC 0.097 BC 0.126
Ep -0.261 Ep -0.288 Ep -0.279 Ecl -0.145 Met 0.077 Ecl 0.093
HSat -0.326 DRN -0.297 DRN -0.283 DRN -0.363 Ecl 0.047 Arg 0.076
HSat -0.326 Ars -0.304 HSat -0.387 DRN -0.091 Theb 0.057
HSat -0.404 Ars -0.390 HSat -0.102 DRN -0.092
  Ep -0.451 Ars -0.187 Ars -0.195
Ep -0.188 HSat -0.205
Ep -0.338
Table 7. 
Intensity of text reuse for select pairs of hexameter texts with post-Vergilian epics as target text (Ovid’s Metamorphoses, Lucan’s Bellum Civile, Valerius Flaccus’ Argonautica, Statius’ Thebaid and Achilleid, and Silius Italicus’ Punica).
Figure 11. 
Intensity of text reuse for 276 pairs of hexameter texts from the 1st century BCE to the 6th century CE, determined by comparing composite counts of high scoring results in Tesserae searches with expected counts based on a text lengths. Reuse intensity is sorted chronologically by source text (with the set of all pairs for comparison).
Figure 12. 
Intensity of text reuse for 276 pairs of hexameter texts from the 1st century BCE to the 6th century CE, determined by comparing composite counts of high scoring results in Tesserae searches with expected counts based on a text lengths. Reuse intensity is sorted chronologically by target text (with the set of all pairs for comparison).
Figure 13. 
Intensity of text reuse for pairs of hexameter texts written by the same author.
Figure 14. 
Intensity of text reuse for pairs of hexameter texts within the same genre (didactic, epic/panegyric, and satire), or pairs comprising one epic/panegyric and one satiric text. The didactic genre comprises: DNR, Georg, and, Astr. The epic/panegyric genre comprises: Aen, Met, BC, Ilias, Arg, Theb, Ach, Pun, Rapt, Hon, Gild, Stil, and Joh. The satiric genre comprises: HSat, PSat, and JSat.
Figure 15. 
Intensity of text reuse for select pairs of hexameter texts with post-Vergilian epics as target text (Ovid’s Metamorphoses, Lucan’s Bellum Civile, Valerius Flaccus’ Argonautica, Statius’ Thebaid and Achilleid, and Silius Italicus’ Punica).
Source Target C7 C8 C9 C10 C11 Cobs r
DRN Ecl 911 193 28 1 0 129.9 -0.134
DRN HSat 2171 552 100 5 0 380.0 -0.183
DRN Georg 2643 894 169 8 0 571.8 0.230
DRN Ep 1414 358 70 4 0 256.7 -0.139
DRN Aen 11060 3350 790 92 0 2755.7 -0.015
DRN Ars 407 74 16 2 0 68.6 -0.052
DRN Met 12958 3726 827 100 0 3036.4 -0.164
DRN Astr 5380 1458 331 10 0 1030.2 0.023
DRN PSat 601 84 16 2 0 81.9 -0.316
DRN BC 8160 2318 464 22 0 1591.4 -0.297
DRN Ilias 1089 254 39 3 0 177.4 -0.017
DRN Arg 5904 1416 351 15 0 1102.3 -0.283
DRN Theb 9682 2443 520 44 0 1901.1 -0.363
DRN Ach 1117 260 42 3 0 183.4 -0.091
DRN Pun 12722 3892 907 105 0 3171.5 -0.092
DRN JSat 3685 955 188 5 0 645.5 -0.330
DRN HE 3353 883 132 4 0 548.0 -0.221
DRN Mos 377 86 14 1 0 61.2 -0.111
DRN Rapt 1028 235 49 2 0 173.4 -0.111
DRN Hon 565 124 27 1 0 93.6 -0.042
DRN Gild 387 65 9 0 0 45.8 -0.484
DRN Stil 1074 282 49 1 0 180.3 -0.170
DRN Joh 4842 1393 306 13 0 978.6 -0.101
Ecl HSat 201 33 6 0 0 25.0 -0.066
Ecl Georg 374 98 5 0 0 48.5 0.603
Ecl Ep 130 27 1 0 0 14.5 -0.171
Ecl Aen 1222 250 53 4 0 204.4 0.224
Ecl Ars 39 3 0 0 0 2.9 -0.370
Ecl Met 1482 325 55 12 0 288.5 0.323
Ecl Astr 501 93 24 1 0 79.9 0.307
Ecl PSat 56 7 0 0 0 4.8 -0.316
Ecl BC 801 146 23 2 0 114.3 -0.089
Ecl Ilias 138 19 1 0 0 13.2 0.224
Ecl Arg 693 116 13 1 0 85.1 -0.003
Ecl Theb 1106 175 29 1 0 138.1 -0.145
Ecl Ach 128 22 0 0 0 12.3 0.047
Ecl Pun 1312 261 45 7 0 222.9 0.093
Ecl JSat 413 83 9 0 0 51.4 -0.021
Ecl HE 330 56 5 0 0 36.5 -0.089
Ecl Mos 54 3 0 0 0 3.8 -0.058
Ecl Rapt 117 20 0 0 0 11.2 -0.009
Ecl Hon 51 5 0 0 0 4.1 -0.341
Ecl Gild 30 5 0 0 0 2.8 -0.422
Ecl Stil 137 26 0 0 0 13.7 0.094
Ecl Joh 524 99 5 0 0 57.3 -0.098
HSat Georg 583 176 20 0 0 93.0 0.037
HSat Ep 490 126 19 0 0 75.4 0.259
HSat Aen 2638 674 111 3 0 432.7 -0.243
HSat Ars 151 23 1 0 0 14.8 0.041
HSat Met 3107 780 112 7 0 509.6 -0.326
HSat Astr 1090 282 31 0 0 156.9 -0.236
HSat PSat 196 45 6 0 0 27.4 0.210
HSat BC 1983 424 58 6 0 304.8 -0.326
HSat Ilias 239 56 3 0 0 29.3 -0.195
HSat Arg 1419 329 31 1 0 192.6 -0.404
HSat Theb 2400 551 67 6 0 366.3 -0.387
HSat Ach 254 81 3 0 0 35.8 -0.102
HSat Pun 3151 839 108 13 0 559.1 -0.205
HSat JSat 1167 292 37 1 0 175.9 -0.007
HSat HE 769 190 19 0 0 105.8 -0.242
HSat Mos 87 20 1 0 0 10.5 -0.253
HSat Rapt 218 49 0 0 0 23.5 -0.485
HSat Hon 125 18 2 0 0 13.2 -0.376
HSat Gild 126 19 0 0 0 11.5 -0.243
HSat Stil 257 68 3 0 0 33.0 -0.244
HSat Joh 1052 287 30 0 0 154.9 -0.322
Georg Ep 413 114 6 0 0 55.3 -0.045
Georg Aen 4150 1276 275 42 4 1974.8 1.280
Georg Ars 140 16 1 0 0 12.6 -0.114
Georg Met 4460 1415 251 28 1 1228.6 0.560
Georg Astr 1578 473 75 1 0 278.1 0.342
Georg PSat 158 34 2 0 0 18.7 -0.164
Georg BC 2876 794 140 18 0 596.6 0.351
Georg Ilias 372 111 2 0 0 48.3 0.310
Georg Arg 2341 584 108 2 0 386.1 0.297
Georg Theb 3433 965 144 14 0 645.8 0.186
Georg Ach 428 83 3 0 0 46.2 0.160
Georg Pun 4728 1489 245 32 0 1052.0 0.433
Georg JSat 1104 329 31 1 0 174.6 -0.009
Georg HE 975 313 33 0 0 159.3 0.172
Georg Mos 159 28 2 0 0 17.4 0.260
Georg Rapt 379 126 15 0 0 65.1 0.538
Georg Hon 204 42 3 0 0 24.1 0.232
Georg Gild 162 39 1 0 0 19.1 0.268
Georg Stil 353 96 6 0 0 47.8 0.132
Georg Joh 1677 473 94 1 0 302.8 0.355
Ep Aen 1658 420 56 5 0 276.9 -0.216
Ep Ars 134 22 0 0 0 12.6 0.354
Ep Met 2052 545 67 5 0 338.6 -0.261
Ep Astr 860 205 15 0 0 110.4 -0.114
Ep PSat 116 25 1 0 0 13.3 -0.040
Ep BC 1437 278 46 1 0 197.2 -0.288
Ep Ilias 150 39 0 0 0 17.4 -0.245
Ep Arg 951 211 34 0 0 136.0 -0.279
Ep Theb 1496 372 32 2 0 214.0 -0.451
Ep Ach 188 43 0 0 0 20.5 -0.188
Ep Pun 1803 460 79 3 0 304.7 -0.338
Ep JSat 705 219 21 0 0 110.7 0.003
Ep HE 513 114 5 0 0 60.1 -0.336
Ep Mos 75 14 0 0 0 7.5 -0.121
Ep Rapt 150 41 3 0 0 20.8 -0.133
Ep Hon 94 19 1 0 0 10.7 -0.117
Ep Gild 57 17 0 0 0 7.1 -0.253
Ep Stil 199 47 2 0 0 24.0 -0.090
Ep Joh 742 164 19 0 0 98.4 -0.301
Aen Ars 539 85 15 1 0 71.3 -0.356
Aen Met 21610 6172 1364 250 7 7156.5 0.350
Aen Astr 6658 1763 437 35 0 1435.2 0.011
Aen PSat 735 131 21 0 0 92.6 -0.537
Aen BC 13863 3157 815 99 0 2942.2 -0.026
Aen Ilias 2361 670 112 10 0 460.9 0.594
Aen Arg 12214 3071 647 99 0 2660.2 0.255
Aen Theb 18667 4816 1166 190 3 5196.9 0.299
Aen Ach 2196 511 87 8 0 378.1 0.289
Aen Pun 26063 7011 1720 323 7 8415.5 0.540
Aen JSat 5113 1252 299 19 0 993.2 -0.243
Aen HE 4656 1236 255 19 0 919.3 -0.047
Aen Mos 623 114 28 3 0 108.2 0.115
Aen Rapt 1674 494 83 14 0 378.1 0.326
Aen Hon 910 182 41 2 0 146.7 0.064
Aen Gild 773 151 24 2 0 114.9 0.092
Aen Stil 1761 411 73 7 0 310.4 0.030
Aen Joh 9050 2482 550 59 0 1997.9 0.269
Ars Met 681 83 15 2 0 85.3 -0.112
Ars Astr 213 58 8 0 0 33.3 0.213
Ars PSat 37 4 0 0 0 3.0 0.008
Ars BC 398 56 10 1 0 51.7 -0.100
Ars Ilias 59 3 0 0 0 4.1 -0.171
Ars Arg 268 33 6 0 0 28.8 -0.304
Ars Theb 515 57 7 0 0 49.4 -0.390
Ars Ach 50 7 0 0 0 4.4 -0.187
Ars Pun 642 109 15 0 0 76.3 -0.195
Ars JSat 229 39 4 0 0 25.9 0.078
Ars HE 164 27 3 0 0 18.5 0.013
Ars Mos 24 1 0 0 0 1.6 -0.131
Ars Rapt 49 5 0 0 0 3.9 -0.272
Ars Hon 28 1 0 0 0 1.8 -0.351
Ars Gild 15 0 0 0 0 0.9 -0.834
Ars Stil 66 15 0 0 0 7.2 0.228
Ars Joh 207 29 2 0 0 20.4 -0.348
Met Astr 8646 2366 466 39 0 1738.9 -0.064
Met PSat 797 161 22 6 0 141.6 -0.379
Met BC 16737 3936 966 131 6 5000.8 0.238
Met Ilias 2497 662 74 14 1 681.8 0.719
Met Arg 12279 2899 622 75 1 2677.2 -0.006
Met Theb 19745 5002 1015 165 4 5220.1 0.037
Met Ach 2330 639 78 7 0 399.3 0.077
Met Pun 24950 6621 1564 284 5 7407.3 0.146
Met JSat 6383 1685 328 37 0 1305.5 -0.236
Met HE 5307 1420 235 20 0 984.3 -0.246
Met Mos 814 135 26 6 1 368.5 1.073
Met Rapt 1971 548 97 9 0 389.8 0.089
Met Hon 992 260 29 5 0 175.8 -0.022
Met Gild 775 192 23 3 0 129.5 -0.055
Met Stil 2073 597 84 10 0 400.0 0.017
Met Joh 9569 2604 515 29 0 1831.5 -0.085
Astr PSat 305 59 2 0 0 32.8 -0.468
Astr BC 6009 1465 239 21 0 1045.0 0.048
Astr Ilias 732 161 17 0 0 95.2 0.125
Astr Arg 3871 867 171 3 0 606.8 -0.114
Astr Theb 6224 1506 257 16 0 1053.1 -0.189
Astr Ach 760 166 17 0 0 97.9 0.047
Astr Pun 8545 2134 439 30 0 1597.4 -0.013
Astr JSat 2253 554 91 3 0 363.6 -0.139
Astr HE 1916 533 61 0 0 290.7 -0.090
Astr Mos 314 59 5 0 0 36.3 0.130
Astr Rapt 657 151 17 0 0 88.6 -0.016
Astr Hon 407 70 8 0 0 47.1 0.036
Astr Gild 304 47 4 0 0 32.0 -0.077
Astr Stil 731 159 21 0 0 98.7 -0.007
Astr Joh 3184 870 154 4 0 557.3 0.101
PSat BC 564 79 12 1 0 68.4 -0.300
PSat Ilias 63 7 0 0 0 5.2 -0.406
PSat Arg 434 63 12 0 0 51.1 -0.211
PSat Theb 698 113 11 1 0 82.7 -0.354
PSat Ach 60 14 0 0 0 6.6 -0.273
PSat Pun 891 150 28 1 0 119.1 -0.230
PSat JSat 343 79 7 0 0 44.4 0.137
PSat HE 197 33 0 0 0 18.7 -0.454
PSat Mos 31 3 0 0 0 2.5 -0.185
PSat Rapt 62 5 0 0 0 4.7 -0.579
PSat Hon 30 6 0 0 0 3.1 -0.315
PSat Gild 28 2 0 0 0 2.1 -0.444
PSat Stil 77 16 0 0 0 8.0 -0.139
PSat Joh 250 46 5 0 0 29.7 -0.453
BC Ilias 1387 294 25 4 0 195.8 0.028
BC Arg 8571 1837 391 48 0 1597.4 0.035
BC Theb 14282 3067 631 85 0 2674.1 -0.075
BC Ach 1607 303 48 4 0 233.5 0.097
BC Pun 18677 4366 957 147 1 4161.6 0.126
BC JSat 4549 1061 211 10 0 773.3 -0.203
BC HE 3518 851 138 8 0 581.4 -0.215
BC Mos 463 76 19 0 0 62.7 -0.142
BC Rapt 1458 334 47 9 0 262.3 0.250
BC Hon 920 160 22 4 0 135.9 0.278
BC Gild 580 133 23 4 0 111.3 0.351
BC Stil 1645 357 59 9 0 290.2 0.253
BC Joh 7466 1754 336 23 0 1303.1 0.132
Ilias Arg 1150 237 30 1 0 155.5 0.389
Ilias Theb 1818 380 45 3 0 253.6 0.252
Ilias Ach 234 36 0 0 0 21.5 0.064
Ilias Pun 2581 582 70 6 0 386.6 0.396
Ilias JSat 465 107 17 0 0 67.7 0.279
Ilias HE 484 106 10 0 0 61.6 0.433
Ilias Mos 50 12 0 0 0 5.6 0.076
Ilias Rapt 158 32 0 0 0 16.3 0.045
Ilias Hon 88 10 0 0 0 7.3 -0.303
Ilias Gild 77 18 0 0 0 8.5 0.223
Ilias Stil 177 35 0 0 0 18.0 -0.137
Ilias Joh 977 212 29 3 0 151.6 0.120
Arg Theb 11371 2503 535 45 0 2032.8 -0.290
Arg Ach 1304 297 31 2 0 185.1 0.152
Arg Pun 14178 3236 650 68 0 2618.2 0.067
Arg JSat 2895 682 118 4 0 462.5 0.036
Arg HE 2731 614 121 0 0 415.7 0.024
Arg Mos 357 50 4 0 0 35.7 0.457
Arg Rapt 1099 224 31 0 0 144.4 0.097
Arg Hon 538 96 11 1 0 69.7 0.157
Arg Gild 430 82 14 0 0 57.1 -0.039
Arg Stil 1120 226 22 1 0 143.3 0.663
Arg Joh 4622 1069 171 9 0 733.0 -0.030
Theb Ach 2283 517 58 2 0 317.8 0.141
Theb Pun 22806 5275 1076 165 2 5062.7 0.057
Theb JSat 4733 1232 170 13 0 800.1 -0.434
Theb HE 4047 989 184 10 0 701.3 -0.293
Theb Mos 612 95 20 1 0 82.8 -0.128
Theb Rapt 1844 500 53 5 0 302.6 0.128
Theb Hon 972 200 28 2 0 141.3 0.052
Theb Gild 727 130 17 1 0 94.2 -0.081
Theb Stil 1836 395 60 6 0 291.8 -0.006
Theb Joh 7759 1900 303 22 0 1313.5 -0.125
Ach Pun 2631 614 91 7 0 423.9 0.410
Ach JSat 559 115 10 0 0 67.9 -0.068
Ach HE 448 87 6 0 0 51.3 -0.076
Ach Mos 68 10 0 0 0 6.1 0.104
Ach Rapt 207 45 2 0 0 24.0 0.426
Ach Hon 112 16 0 0 0 10.0 0.238
Ach Gild 68 13 1 0 0 7.8 0.263
Ach Stil 226 45 1 0 0 24.1 0.331
Ach Joh 881 194 27 1 0 127.4 0.375
Pun JSat 6378 1625 296 26 0 1190.6 -0.298
Pun HE 5321 1403 262 26 0 1046.0 -0.154
Pun Mos 755 133 21 5 0 125.6 0.028
Pun Rapt 2074 573 76 11 0 392.9 0.128
Pun Hon 1168 247 31 5 0 185.0 0.060
Pun Gild 957 163 31 2 0 135.1 0.018
Pun Stil 2204 544 73 6 0 359.4 -0.059
Pun Joh 11414 2598 525 43 0 2034.1 0.051
JSat HE 1386 361 47 1 0 213.9 -0.273
JSat Mos 191 43 5 0 0 25.6 -0.094
JSat Rapt 464 131 15 0 0 71.1 -0.113
JSat Hon 300 67 10 0 0 42.3 0.053
JSat Gild 222 42 6 0 0 28.2 -0.081
JSat Stil 592 143 12 0 0 78.1 -0.117
JSat Joh 2486 594 106 3 0 401.0 -0.104
HE Mos 165 35 2 0 0 19.3 -0.079
HE Rapt 430 102 11 0 0 58.6 -0.010
HE Hon 244 43 3 0 0 26.7 -0.112
HE Gild 202 44 3 0 0 24.5 0.075
HE Stil 470 117 11 0 0 64.3 -0.016
HE Joh 2321 639 105 8 0 432.1 0.267
Mos Rapt 62 5 1 0 0 5.7 0.153
Mos Hon 44 5 0 0 0 3.6 0.395
Mos Gild 34 0 0 0 0 2.0 0.042
Mos Stil 77 11 0 0 0 6.9 0.247
Mos Joh 263 43 10 0 0 34.8 0.324
Rapt Hon 104 27 0 0 0 12.0 0.243
Rapt Gild 100 13 0 0 0 8.7 0.461
Rapt Stil 193 53 0 0 0 23.0 0.404
Rapt Joh 845 198 21 0 0 114.0 0.302
Hon Gild 59 8 0 0 0 5.2 0.634
Hon Stil 133 38 0 0 0 16.2 0.716
Hon Joh 472 89 11 0 0 58.1 0.372
Gild Stil 100 21 0 0 0 10.5 0.575
Gild Joh 402 74 6 0 0 45.7 0.427
Stil Joh 862 182 24 0 0 114.4 0.199
Table 8. 
Results of Tesserae searches of 276 pairs of hexameter texts from the 1st century BCE to the 6th century CE, sorted chronologically by source text. Results include: raw counts of score 7, 8, 9, 10, and 11; composite counts calculated from the raw counts using a combination of linear regressions and principal component analysis; and text reuse intensity, determined by comparing the composite counts with expected counts based on a text lengths.
Source Target C7 C8 C9 C10 C11 Cobs r
DRN Ecl 911 193 28 1 0 129.9 -0.134
DRN HSat 2171 552 100 5 0 380.0 -0.183
Ecl HSat 201 33 6 0 0 25.0 -0.066
DRN Georg 2643 894 169 8 0 571.8 0.230
Ecl Georg 374 98 5 0 0 48.5 0.603
HSat Georg 583 176 20 0 0 93.0 0.037
DRN Ep 1414 358 70 4 0 256.7 -0.139
Ecl Ep 130 27 1 0 0 14.5 -0.171
HSat Ep 490 126 19 0 0 75.4 0.259
Georg Ep 413 114 6 0 0 55.3 -0.045
DRN Aen 11060 3350 790 92 0 2755.7 -0.015
Ecl Aen 1222 250 53 4 0 204.4 0.224
HSat Aen 2638 674 111 3 0 432.7 -0.243
Georg Aen 4150 1276 275 42 4 1974.8 1.280
Ep Aen 1658 420 56 5 0 276.9 -0.216
DRN Ars 407 74 16 2 0 68.6 -0.052
Ecl Ars 39 3 0 0 0 2.9 -0.370
HSat Ars 151 23 1 0 0 14.8 0.041
Georg Ars 140 16 1 0 0 12.6 -0.114
Ep Ars 134 22 0 0 0 12.6 0.354
Aen Ars 539 85 15 1 0 71.3 -0.356
DRN Met 12958 3726 827 100 0 3036.4 -0.164
Ecl Met 1482 325 55 12 0 288.5 0.323
HSat Met 3107 780 112 7 0 509.6 -0.326
Georg Met 4460 1415 251 28 1 1228.6 0.560
Ep Met 2052 545 67 5 0 338.6 -0.261
Aen Met 21610 6172 1364 250 7 7156.5 0.350
Ars Met 681 83 15 2 0 85.3 -0.112
DRN Astr 5380 1458 331 10 0 1030.2 0.023
Ecl Astr 501 93 24 1 0 79.9 0.307
HSat Astr 1090 282 31 0 0 156.9 -0.236
Georg Astr 1578 473 75 1 0 278.1 0.342
Ep Astr 860 205 15 0 0 110.4 -0.114
Aen Astr 6658 1763 437 35 0 1435.2 0.011
Ars Astr 213 58 8 0 0 33.3 0.213
Met Astr 8646 2366 466 39 0 1738.9 -0.064
DRN PSat 601 84 16 2 0 81.9 -0.316
Ecl PSat 56 7 0 0 0 4.8 -0.316
HSat PSat 196 45 6 0 0 27.4 0.210
Georg PSat 158 34 2 0 0 18.7 -0.164
Ep PSat 116 25 1 0 0 13.3 -0.040
Aen PSat 735 131 21 0 0 92.6 -0.537
Ars PSat 37 4 0 0 0 3.0 0.008
Met PSat 797 161 22 6 0 141.6 -0.379
Astr PSat 305 59 2 0 0 32.8 -0.468
DRN BC 8160 2318 464 22 0 1591.4 -0.297
Ecl BC 801 146 23 2 0 114.3 -0.089
HSat BC 1983 424 58 6 0 304.8 -0.326
Georg BC 2876 794 140 18 0 596.6 0.351
Ep BC 1437 278 46 1 0 197.2 -0.288
Aen BC 13863 3157 815 99 0 2942.2 -0.026
Ars BC 398 56 10 1 0 51.7 -0.100
Met BC 16737 3936 966 131 6 5000.8 0.238
Astr BC 6009 1465 239 21 0 1045.0 0.048
PSat BC 564 79 12 1 0 68.4 -0.300
DRN Ilias 1089 254 39 3 0 177.4 -0.017
Ecl Ilias 138 19 1 0 0 13.2 0.224
HSat Ilias 239 56 3 0 0 29.3 -0.195
Georg Ilias 372 111 2 0 0 48.3 0.310
Ep Ilias 150 39 0 0 0 17.4 -0.245
Aen Ilias 2361 670 112 10 0 460.9 0.594
Ars Ilias 59 3 0 0 0 4.1 -0.171
Met Ilias 2497 662 74 14 1 681.8 0.719
Astr Ilias 732 161 17 0 0 95.2 0.125
PSat Ilias 63 7 0 0 0 5.2 -0.406
BC Ilias 1387 294 25 4 0 195.8 0.028
DRN Arg 5904 1416 351 15 0 1102.3 -0.283
Ecl Arg 693 116 13 1 0 85.1 -0.003
HSat Arg 1419 329 31 1 0 192.6 -0.404
Georg Arg 2341 584 108 2 0 386.1 0.297
Ep Arg 951 211 34 0 0 136.0 -0.279
Aen Arg 12214 3071 647 99 0 2660.2 0.255
Ars Arg 268 33 6 0 0 28.8 -0.304
Met Arg 12279 2899 622 75 1 2677.2 -0.006
Astr Arg 3871 867 171 3 0 606.8 -0.114
PSat Arg 434 63 12 0 0 51.1 -0.211
BC Arg 8571 1837 391 48 0 1597.4 0.035
Ilias Arg 1150 237 30 1 0 155.5 0.389
DRN Theb 9682 2443 520 44 0 1901.1 -0.363
Ecl Theb 1106 175 29 1 0 138.1 -0.145
HSat Theb 2400 551 67 6 0 366.3 -0.387
Georg Theb 3433 965 144 14 0 645.8 0.186
Ep Theb 1496 372 32 2 0 214.0 -0.451
Aen Theb 18667 4816 1166 190 3 5196.9 0.299
Ars Theb 515 57 7 0 0 49.4 -0.390
Met Theb 19745 5002 1015 165 4 5220.1 0.037
Astr Theb 6224 1506 257 16 0 1053.1 -0.189
PSat Theb 698 113 11 1 0 82.7 -0.354
BC Theb 14282 3067 631 85 0 2674.1 -0.075
Ilias Theb 1818 380 45 3 0 253.6 0.252
Arg Theb 11371 2503 535 45 0 2032.8 0.064
DRN Ach 1117 260 42 3 0 183.4 -0.091
Ecl Ach 128 22 0 0 0 12.3 0.047
HSat Ach 254 81 3 0 0 35.8 -0.102
Georg Ach 428 83 3 0 0 46.2 0.160
Ep Ach 188 43 0 0 0 20.5 -0.188
Aen Ach 2196 511 87 8 0 378.1 0.289
Ars Ach 50 7 0 0 0 4.4 -0.187
Met Ach 2330 639 78 7 0 399.3 0.077
Astr Ach 760 166 17 0 0 97.9 0.047
PSat Ach 60 14 0 0 0 6.6 -0.273
BC Ach 1607 303 48 4 0 233.5 0.097
Ilias Ach 234 36 0 0 0 21.5 0.396
Arg Ach 1304 297 31 2 0 185.1 0.279
Theb Ach 2283 517 58 2 0 317.8 0.141
DRN Pun 12722 3892 907 105 0 3171.5 -0.092
Ecl Pun 1312 261 45 7 0 222.9 0.093
HSat Pun 3151 839 108 13 0 559.1 -0.205
Georg Pun 4728 1489 245 32 0 1052.0 0.433
Ep Pun 1803 460 79 3 0 304.7 -0.338
Aen Pun 26063 7011 1720 323 7 8415.5 0.540
Ars Pun 642 109 15 0 0 76.3 -0.195
Met Pun 24950 6621 1564 284 5 7407.3 0.146
Astr Pun 8545 2134 439 30 0 1597.4 -0.013
PSat Pun 891 150 28 1 0 119.1 -0.230
BC Pun 18677 4366 957 147 1 4161.6 0.126
Ilias Pun 2581 582 70 6 0 386.6 0.433
Arg Pun 14178 3236 650 68 0 2618.2 0.076
Theb Pun 22806 5275 1076 165 2 5062.7 0.057
Ach Pun 2631 614 91 7 0 423.9 0.410
DRN JSat 3685 955 188 5 0 645.5 -0.330
Ecl JSat 413 83 9 0 0 51.4 -0.021
HSat JSat 1167 292 37 1 0 175.9 -0.007
Georg JSat 1104 329 31 1 0 174.6 -0.009
Ep JSat 705 219 21 0 0 110.7 0.003
Aen JSat 5113 1252 299 19 0 993.2 -0.243
Ars JSat 229 39 4 0 0 25.9 0.078
Met JSat 6383 1685 328 37 0 1305.5 -0.236
Astr JSat 2253 554 91 3 0 363.6 -0.139
PSat JSat 343 79 7 0 0 44.4 0.137
BC JSat 4549 1061 211 10 0 773.3 -0.203
Ilias JSat 465 107 17 0 0 67.7 0.045
Arg JSat 2895 682 118 4 0 462.5 -0.303
Theb JSat 4733 1232 170 13 0 800.1 -0.434
Ach JSat 559 115 10 0 0 67.9 -0.068
Pun JSat 6378 1625 296 26 0 1190.6 -0.298
DRN HE 3353 883 132 4 0 548.0 -0.221
Ecl HE 330 56 5 0 0 36.5 -0.089
HSat HE 769 190 19 0 0 105.8 -0.242
Georg HE 975 313 33 0 0 159.3 0.172
Ep HE 513 114 5 0 0 60.1 -0.336
Aen HE 4656 1236 255 19 0 919.3 -0.047
Ars HE 164 27 3 0 0 18.5 0.013
Met HE 5307 1420 235 20 0 984.3 -0.246
Astr HE 1916 533 61 0 0 290.7 -0.090
PSat HE 197 33 0 0 0 18.7 -0.454
BC HE 3518 851 138 8 0 581.4 -0.215
Ilias HE 484 106 10 0 0 61.6 0.223
Arg HE 2731 614 121 0 0 415.7 -0.137
Theb HE 4047 989 184 10 0 701.3 -0.293
Ach HE 448 87 6 0 0 51.3 -0.076
Pun HE 5321 1403 262 26 0 1046.0 -0.154
JSat HE 1386 361 47 1 0 213.9 -0.273
DRN Mos 377 86 14 1 0 61.2 -0.111
Ecl Mos 54 3 0 0 0 3.8 -0.058
HSat Mos 87 20 1 0 0 10.5 -0.253
Georg Mos 159 28 2 0 0 17.4 0.260
Ep Mos 75 14 0 0 0 7.5 -0.121
Aen Mos 623 114 28 3 0 108.2 0.115
Ars Mos 24 1 0 0 0 1.6 -0.131
Met Mos 814 135 26 6 1 368.5 1.073
Astr Mos 314 59 5 0 0 36.3 0.130
PSat Mos 31 3 0 0 0 2.5 -0.185
BC Mos 463 76 19 0 0 62.7 -0.142
Ilias Mos 50 12 0 0 0 5.6 0.120
Arg Mos 357 50 4 0 0 35.7 -0.290
Theb Mos 612 95 20 1 0 82.8 -0.128
Ach Mos 68 10 0 0 0 6.1 0.104
Pun Mos 755 133 21 5 0 125.6 0.028
JSat Mos 191 43 5 0 0 25.6 -0.094
HE Mos 165 35 2 0 0 19.3 -0.079
DRN Rapt 1028 235 49 2 0 173.4 -0.111
Ecl Rapt 117 20 0 0 0 11.2 -0.009
HSat Rapt 218 49 0 0 0 23.5 -0.485
Georg Rapt 379 126 15 0 0 65.1 0.538
Ep Rapt 150 41 3 0 0 20.8 -0.133
Aen Rapt 1674 494 83 14 0 378.1 0.326
Ars Rapt 49 5 0 0 0 3.9 -0.272
Met Rapt 1971 548 97 9 0 389.8 0.089
Astr Rapt 657 151 17 0 0 88.6 -0.016
PSat Rapt 62 5 0 0 0 4.7 -0.579
BC Rapt 1458 334 47 9 0 262.3 0.250
Ilias Rapt 158 32 0 0 0 16.3 0.152
Arg Rapt 1099 224 31 0 0 144.4 0.067
Theb Rapt 1844 500 53 5 0 302.6 0.128
Ach Rapt 207 45 2 0 0 24.0 0.426
Pun Rapt 2074 573 76 11 0 392.9 0.128
JSat Rapt 464 131 15 0 0 71.1 -0.113
HE Rapt 430 102 11 0 0 58.6 -0.010
Mos Rapt 62 5 1 0 0 5.7 0.153
DRN Hon 565 124 27 1 0 93.6 -0.042
Ecl Hon 51 5 0 0 0 4.1 -0.341
HSat Hon 125 18 2 0 0 13.2 -0.376
Georg Hon 204 42 3 0 0 24.1 0.232
Ep Hon 94 19 1 0 0 10.7 -0.117
Aen Hon 910 182 41 2 0 146.7 0.064
Ars Hon 28 1 0 0 0 1.8 -0.351
Met Hon 992 260 29 5 0 175.8 -0.022
Astr Hon 407 70 8 0 0 47.1 0.036
PSat Hon 30 6 0 0 0 3.1 -0.315
BC Hon 920 160 22 4 0 135.9 0.278
Ilias Hon 88 10 0 0 0 7.3 0.036
Arg Hon 538 96 11 1 0 69.7 0.024
Theb Hon 972 200 28 2 0 141.3 0.052
Ach Hon 112 16 0 0 0 10.0 0.238
Pun Hon 1168 247 31 5 0 185.0 0.060
JSat Hon 300 67 10 0 0 42.3 0.053
HE Hon 244 43 3 0 0 26.7 -0.112
Mos Hon 44 5 0 0 0 3.6 0.395
Rapt Hon 104 27 0 0 0 12.0 0.461
DRN Gild 387 65 9 0 0 45.8 -0.484
Ecl Gild 30 5 0 0 0 2.8 -0.422
HSat Gild 126 19 0 0 0 11.5 -0.243
Georg Gild 162 39 1 0 0 19.1 0.268
Ep Gild 57 17 0 0 0 7.1 -0.253
Aen Gild 773 151 24 2 0 114.9 0.092
Ars Gild 15 0 0 0 0 0.9 -0.834
Met Gild 775 192 23 3 0 129.5 -0.055
Astr Gild 304 47 4 0 0 32.0 -0.077
PSat Gild 28 2 0 0 0 2.1 -0.444
BC Gild 580 133 23 4 0 111.3 0.351
Ilias Gild 77 18 0 0 0 8.5 0.457
Arg Gild 430 82 14 0 0 57.1 0.097
Theb Gild 727 130 17 1 0 94.2 -0.081
Ach Gild 68 13 1 0 0 7.8 0.263
Pun Gild 957 163 31 2 0 135.1 0.018
JSat Gild 222 42 6 0 0 28.2 -0.081
HE Gild 202 44 3 0 0 24.5 0.075
Mos Gild 34 0 0 0 0 2.0 0.042
Rapt Gild 100 13 0 0 0 8.7 0.404
Hon Gild 59 8 0 0 0 5.2 0.634
DRN Stil 1074 282 49 1 0 180.3 -0.170
Ecl Stil 137 26 0 0 0 13.7 0.094
HSat Stil 257 68 3 0 0 33.0 -0.244
Georg Stil 353 96 6 0 0 47.8 0.132
Ep Stil 199 47 2 0 0 24.0 -0.090
Aen Stil 1761 411 73 7 0 310.4 0.030
Ars Stil 66 15 0 0 0 7.2 0.228
Met Stil 2073 597 84 10 0 400.0 0.017
Astr Stil 731 159 21 0 0 98.7 -0.007
PSat Stil 77 16 0 0 0 8.0 -0.139
BC Stil 1645 357 59 9 0 290.2 0.253
Ilias Stil 177 35 0 0 0 18.0 0.157
Arg Stil 1120 226 22 1 0 143.3 -0.039
Theb Stil 1836 395 60 6 0 291.8 -0.006
Ach Stil 226 45 1 0 0 24.1 0.331
Pun Stil 2204 544 73 6 0 359.4 -0.059
JSat Stil 592 143 12 0 0 78.1 -0.117
HE Stil 470 117 11 0 0 64.3 -0.016
Mos Stil 77 11 0 0 0 6.9 0.247
Rapt Stil 193 53 0 0 0 23.0 0.324
Hon Stil 133 38 0 0 0 16.2 0.716
Gild Stil 100 21 0 0 0 10.5 0.575
DRN Joh 4842 1393 306 13 0 978.6 -0.101
Ecl Joh 524 99 5 0 0 57.3 -0.098
HSat Joh 1052 287 30 0 0 154.9 -0.322
Georg Joh 1677 473 94 1 0 302.8 0.355
Ep Joh 742 164 19 0 0 98.4 -0.301
Aen Joh 9050 2482 550 59 0 1997.9 0.269
Ars Joh 207 29 2 0 0 20.4 -0.348
Met Joh 9569 2604 515 29 0 1831.5 -0.085
Astr Joh 3184 870 154 4 0 557.3 0.101
PSat Joh 250 46 5 0 0 29.7 -0.453
BC Joh 7466 1754 336 23 0 1303.1 0.132
Ilias Joh 977 212 29 3 0 151.6 0.663
Arg Joh 4622 1069 171 9 0 733.0 -0.030
Theb Joh 7759 1900 303 22 0 1313.5 -0.125
Ach Joh 881 194 27 1 0 127.4 0.375
Pun Joh 11414 2598 525 43 0 2034.1 0.051
JSat Joh 2486 594 106 3 0 401.0 -0.104
HE Joh 2321 639 105 8 0 432.1 0.267
Mos Joh 263 43 10 0 0 34.8 0.243
Rapt Joh 845 198 21 0 0 114.0 0.302
Hon Joh 472 89 11 0 0 58.1 0.372
Gild Joh 402 74 6 0 0 45.7 0.427
Stil Joh 862 182 24 0 0 114.4 0.199
Table 9. 
Results of Tesserae searches of 276 pairs of hexameter texts from the 1st century BCE to the 6th century CE, sorted chronologically by target text. Results include: raw counts of score 7, 8, 9, 10, and 11; composite counts calculated from the raw counts using a combination of linear regressions and principal component analysis; and text reuse intensity, determined by comparing the composite counts with expected counts based on a text lengths.

Notes

[1] See, for example, [Hutchinson 2013], [Farrell 2005], and [Hinds 1998] for points of entry to the study of intertextuality in Latin literature.
[2] All translations are by the authors.
[3] Because Latin is a highly inflected language, the same lexeme may occur in many different inflected forms. For example, percutio may appear as percussus ("struck"), percutimus ("we strike"), percusserant ("they had struck"), etc. Traditional literary interpretation may privilege specific morphological forms, such as the opening words of Vergil’s Aeneid (arma uirumque), which are frequently adapted by later poets, but more often the various inflected forms of a lexeme may be considered to be the same. Tesserae converts all inflected forms to a single lemma (e.g., percussus and percussum are treated as percutio) and so does not permit analysis of individual inflected forms.
[4] See section 2.b for discussion of the scoring system.
[5] Recent commentaries (such as [Steiniger 2005], [Micozzi 2007], and [Parkes 2012]) note the verbal parallel with Aeneid 7.550, but do not offer a literary interpretation of the link. Their reticence is symptomatic of the scholarly tendency to privilege certain allusions (here, Aeneid 9.197) over others in interpretation. The impartial automatic searches of Tesserae encourage an interpretive style that is both less hierarchical and less committed to authorial intention.
[6] The dates of texts mostly follow those found in Brill’s New Pauly, and depart in some cases from the dates used by the Tesserae to assign source and target text status for each pair (http://tesserae.caset.buffalo.edu/blog/authors−and−text−dates/). Where necessary, we manually corrected for the switched source and target. Some dates are uncertain; see, e.g., [Zissos 2008, xiv–xvii] on Valerius Flaccus’ Argonautica, or [Gruzelier 1993, xviii–xix] on Claudian’s De Raptu Proserpinae. Alternative datings would affect our results in some cases, since the calculation of the variable cexp depends on which text in a pair is considered the source and which the target. But the overall effect of any plausible change in dating would be small.
[7] The Tesserae repository is extensive but not complete. Relevant hexameter texts unavailable for the study at this writing include, for example, Ennius’ Annales, the Appendix Vergiliana, the Eclogues of Calpurnius Siculus, and the various Latin versions of Aratus’ Phaenomena.
[8] We included Claudian’s De Raptu Proserpinae because it is an important text and because its pentameter preface is short compared to the text as a whole (69 out of 6991 words), and therefore unlikely to noticeably affect our results.
[9] Ausonius’ Precationes, Ordo Urbium Nobilium, and Cento Nuptialis (see section 3.c.iv), and Claudian’s In Consulatum Olybrii et Probini.
[10] False lemma matches also sometimes occur, such as Vergil, Georgics 4.308 ossibus umor ~ Statius, Thebaid 4.698 oraumor. Here ossibus ("bones") and ora ("faces") are inflected forms of two different lexemes, both of which share the lemma os. Since such false matches occur infrequently, we did not expect them to affect the results significantly.
[11] These parameters are explained at http://tess−dev.caset.buffalo.edu/html/help_advanced.php.
[12] The regressions yielded the following formulae:
Figure 2. 
We omitted the intercepts, which provide no useful information, and thus obtained a formula for a composite count:
Figure 3. 
[13] The first principal component had weights
Figure 4. 
This led to, in original scale, the composite count (which accounts for 90.1% of the total variability):
Figure 5. 
Further rescaling it such that the weight for C9 became 1, we obtained:
Figure 6. 
[14] This model was the best of several considered, namely:
Figure 8. 
[15] The r values are also sorted chronologically by source and target in Table 8 and 9. Standardized residuals have been adjusted by the standard deviation of the entire set in order to detect statistical outliers. Standardized residuals greater than |2| are normally considered unusual; standardized residual greater than |3| are normally considered statistical outliers.
[16] Author (HonStil, Hon Gild, EclGeorg,GildStil, section 3.b), genre (PSat - Rapt, 3.b), multiple reuse (MetIlias, IliasJoh, Aen Ilias, Georg Met, Georg Rapt, 3.c.i), and the influence of Vergil (Aen Pun, 3.c.ii).
[17] Jockers observes, "the strength of the author signals in this experiment in fact trumps the signals of individual texts — something intuition does not prepare us for. The classifier [program] is more likely to identify the author of a given text segment than it is to correctly assign that same text segment to its novel of origin."  [Jockers 2013, 93]
[18] The didactic genre comprised: DRN, Georg, and Astr. The epic/panegyric genre comprised: Aen, Met, BC, Ilias, Arg, Theb, Ach, Pun, Rapt, Hon, Gild, Stil, and Joh. The satiric genre comprised: HSat, PSat, and JSat. This partitioning excludes five texts (Ecl, Ep, Ars, HE, Mos) that do not fit into any of the three genres. Including Horace’s Epistles and Ars Poetica in the satiric genre would not alter our conclusions: in fact, the lowest r value in our data set would then comprise an epic/panegyric–satric pair, ArsGild (r = −0.834).
[19] The exceptions were slight: Ilias – JSat (r = 0.053) and JSatHon (r = 0.045).
[20] The average Cobs value for the Aeneid paired with all subsequent target texts is 1876.6, compared to 284.6 for the Georgics.
[21] Its influence grew later on: the text is quoted in the late antique commentary on the Thebaid ascribed to Lactantius Placidus, and became popular in the Middle Ages [Curtius 1953, 49-51].
[22] This is consistent with scholarly observation; see New Pauly s.v. Ilias Latina [Courtney 2016].
[23] For example, see the discussion of the "many mouths" topos [Gowers 2005].
[24] For discussion of the Flavian poets’ gradual return to scholarly favor, see [Dominik 2010].
[25] Given the low residual, it is remarkable that Tesserae searches reported in [Coffee et al. 2012] identified 25% more interpretively significant instances of verbal reuse in the pair AeneidBellum Civile 1 than the standard philological commentaries. Similar studies for pairs with more intense text reuse (e.g., Aeneid Metamorphoses) would presumably be even more successful.
[26] E.g.,

Compared with other writers of Latin epic, [Silius] tends to eschew signposting his intertexts by the technique of "quotation", that is, by repeating complete phrases or other word collocations from earlier poems. He prefers to signal the intertextual connection by alternative means, in particular, by coincidence of situation and detail rather than wording and, occasionally, by more explicit hints.  [Wilson 2004, 225]

[27] Parkes on the Achilleid and Argonautica is an exception [Parkes 2009]. For the Thebaid and Argonautica, see [Lovatt 2015], with bibliography.
[28] The relative dating of these two epics is uncertain. This study has treated the Achilleid as the source, but the two epics may well have been composed concurrently and influenced one another [Ripoll 2015].
[29] Marks argues for "bi-directional influence" between the two works [Marks 2014].

[30] EpArs (r = 0.354), HSatEp (0.259), HSatArs (0.041) vs. HSat – PSat (0.210), HSat – JSat (−0.007), PSat – JSat (0.137).
[31] HSatRapt (r = −0.485), Aen – PSat (r = −0.537), PSatRapt (r = −0.579). The lowest pair, ArsGild (−0.834), was one of three statistical outliers (section 3.a); although we did not class Horace’s Ars Poetica as a satire, it shares has stylistic features of the genre.
[32] Gruber’s comments are representative of a long tradition of Ausonius commentary: "Sprachlich und thematisch ist Vergil stets gegenwärtig. In jahrzehntelanger Lehrtätigkeit, in deren Mitte der Vergilerklärung stand, hat Ausonius diesen Dichter so verinnerlicht, daβ ihm nicht nur seine Worte, sondern die gesamte Thematik seiner Werke zur Verfügung stehen. Aber auch Lukrez, Horaz und Ovid gehören zum sprachlichen Fundus. Von den Autoren der frühen Kaiserzeit ist vor allem Statius sprachliches und thematisches Vorbild. Dazu kommen Lukan, Silius Italicus, Valerius Flaccus, und Martial"  [Gruber 2013, 27-28]. One of the goals of the present study is to place on an objective footing such statements of the relative importance of a given text as an overall verbal resource for its successors.
[33] Hofmann (New Pauly s.v. Corippus, Flavius Cresconius) calls Corippus "the last great practitioner of the Roman epic… in his use of language and his narrative skill," and cites Vergil and Claudian as the poet’s primary classical influences. Juvencus’ Historia Evangelica differs from all other texts in the data set due to its Biblical subject matter, and it should accordingly come as no surprise that exhibits both low rates of reuse and low centrality. Schmidt (New Pauly s.v. Iuvencus, C. Vettius Aquilinus) lists only Vergil as a relevant source for Juvencus. See [Green 2006, 11–14], who observes "roughly speaking, allusions to Vergil outnumber allusions to all other writers combined by at least five to one" (11 n. 63).

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