DHQ: Digital Humanities Quarterly
2016
Volume 10 Number 3
Volume 10 Number 3
Mining Public Discourse for Emerging Dutch Nationalism
Abstract
Historians have argued that nationalism spread from elite groups to larger populations through public media, yet this has never been empirically proven. In this paper, we use digital tools to search for expressions of nationalism in Dutch newspaper discourse in the late nineteenth century by text mining in large newspaper repositories. The absence of emotional nationalist rhetoric in Dutch national newspapers suggests that nationalism in the late nineteenth century was much more subtle than the literature based on elite discourse tells us.
Introduction
In the nineteenth century, the French philosopher Ernest Renan took up an
important question of his day in a lecture at the Sorbonne. His classical text,
which resulted from that lecture,
Qu’est-ce qu’une nation?, is seen as one of the first
attempts to define nations scientifically. Renan disagreed with many before him
who had defined the nation by criteria such as race or ethnic group or common
characteristics. Instead, he defined a nation by the desire of people to belong
together, their willingness to share a mutual past and a common future.
Therefore, he declared, the existence of the nation was based on daily approval
of this shared desire by its members [Renan 1992, 41–4].
Historians since then have offered numerous theories explaining what made
allegiance to the nation-state, or nationalism, possible among groups. Key among
the mechanisms cited are newspapers.
This paper contributes to the existing literature on nationalism by testing the
thesis that asserts the importance of newspapers to rising nationalism. It will
do this by approaching the question in a new way using digital tools. Using text
mining to answer this question is not an attempt to define or redefine
nationalism. Instead we rely on existing literature to establish the outlines of
our investigation including the hypotheses regarding the role of newspapers in
nationalism that we set out to test. Existing literature has primarily based its
study of the nation on elite discourse. As a result, the creation of the modern
nation has been described as the process of the transmission of high culture to
society at large. Because digital tools allow us unprecedented access to the
contents of digitized newspapers, in this paper, we use the affordances of
digital tools to study a less elite view of nationalism in the late nineteenth
century than is found in existing academic literature on the topic.
Indeed, adopting this viewpoint answers the call of many historians. In a recent
essay, John Breuilly highlighted the elite bias of nationalism studies as a
“major deficit” in the field [Breuilly 2012, 23].
According to Breuilly, existing studies focus overwhelmingly on either elite
discourse or on politics. Often, the two concerns are merged into a single
narrative that stresses the importance of elite discourse in shaping the
mind-sets of nationalist politicians. Insofar as a nationalism studies considers
the popular meaning of nationalism and its development within a broader sphere,
this tends to be based on unproven inferences. Yet in the evidence that existing
studies cite – high turnouts at nationalist festivals and ceremonies, the
popular backing of nationalist politicians or the high numbers of volunteers for
military service – one catches glimpses of a larger public audience that not
only responded to but also shaped the meanings of nation and nationalism. We are
concerned in this paper with tracing nationalism as presented to a larger
audience through newspapers. Following Hobsbawm’s earlier assertion, that
nationalism “is constructed essentially from above, but (…) cannot
be understood unless also analyzed from below, that is in terms of the
assumptions, hopes, needs, longings an interest of ordinary
people”
[Hobsbawm 2012, 10], we will use the power of digital methods to investigate nationalism from
below.
Existing theories, such as those by Anderson, Hobsbawm, and Gellner, lead us to
expect nationalism to have been spread in the late nineteenth century through
the frequent presence of telling phrases in newspapers that invoke the greatness
of a nation and its history [Anderson 1983]
[Hobsbawm 2012]
[Gellner 2008]. According to Benedict Anderson, newspapers with
national circulation were crucial to the creation of imagined national
communities by disseminating the idea of nationhood. In his view, the nation
should be understood not as a geographical or political entity, but as an
imagined community united by a “deep, horizontal comradeship” whereby
national co-fellows are believed to constitute a bounded, natural entity.
Anderson argues that the nation emerges out of imaginative contexts of social
and cultural experience. Regular, synchronic readings of daily or weekly
newspapers produced the idea among readers that they shared a set of interests
and were part of an imagined community. Newspapers were thus a chief way that
“ the imagined world is visibly rooted in everyday life”
[Anderson 1983, 7, 25, 36]. Although, as Tim Edensor has
argued, Anderson’s focus on printed media to the exclusion of all else is a very
reductive view of culture, which encompasses much more than just newspapers,
newspapers have consistently been singled out as important to rising nationalism
in the late nineteenth century [Edensor 2002, 7–17]. So it is
very much worth testing the hypothesis that newspapers contributed to
nationalism. Our digital examination of the content of Dutch newspapers is a
crucial contribution to understanding the nature of the “nationalist”
content of newspapers. By studying the spread of nationalist sentiment through
public discourse, we hope to be able to better understand the role of newspapers
in the spread of nationalism.
Theories of nationalism suggested by other authors offer an alternative to the
emphasis on emotional rhetoric. Another model of how nationalism was spread, for
example, is offered by the British social psychologist Michael Billig. He argues
nationalism was spread, not via the impassioned rhetoric of elite discourse, but
by building a common identity through everyday expressions. Instead of the
“passionate and exotic examples” often given of the spread of
nationalism, Billig draws attention to the routine and mundane reproduction of
the idea of the nation that is necessary to maintain it over time. He points,
for example, to the use of national flags in everyday contexts, differentiating
between what he calls the “waved” flags at national sporting events and the
“unwaved flags” that he sees as a more important daily reminder of
national belonging. Thus a person walking into the supermarket and seeing a
national flag on a milk carton, even if they are looking for something else,
will be unconsciously reminded of his national identity. Billing makes the same
argument for the increasing use of pronouns like “we” that are used as a
signifier of “us” as members of the nation and indeed the increasing use of
nations’ names in the public domain. Nationalism, for Billig, is marked by the
fact that phrases like “the economy”, “the government” and “the
countryside” are immediately and unconsciously translated by readers as
“our economy, government and countryside”. This then constitutes an
important part of the way in which nations are naturalised, or
absorbed into a common-sense view about the way the world is. In this way they
are also invested with moral values, which elevate the national over other
social groupings [Billig 1995]
[Skey 2009]. Billig’s notion of banal nationalism supports the
argument of Niek van Sas, who asserts in his well-respected study of nationalism
in the Netherlands, that nationalism was much more subtle in the years around
1900 than we might expect [van Sas 2004, 161–2]. Others have
cited the development and further standardization of language and the use of
certain words and concepts to describe certain events, customs or practices as
national as important contributions that newspapers have made to forging a
national identity [Baycroft 2004, 9–10]
[Lodge 1993, 2–3]. By analysing popular discourse in national
newspapers using digital methods, we want to judge whether emotional nationalist
rhetoric or more banal mechanisms were more important to promulgating the notion
of national belonging through newspapers.
Using digital methods, this paper tests two hypotheses drawn from secondary
literature about the nature of nationalist discourse (emotional or banal) in the
late nineteenth century in national Dutch newspapers. To carry out our test, we
first used topic modelling to try to capture the content of newspaper articles.
We used topic modelling for its ability to produce pseudo-semantic information
in the presence of OCR errors (which beset our corpus and made
tools from corpus linguistics, as discussed below, difficult to use). The fact
that we did not find emotional, nationalist rhetoric in Dutch newspapers in the
late nineteenth century was very revealing, for it suggests that nationalism,
which the literature agrees was present at this time, was expressed in
newspapers not using grandiose, emotional appeals, but in more subtle ways. This
also implies that the emotional nationalism that is so often commented on — and
blamed for leading to the First World War [Clark 2013] — was formed
outside of newspapers and reflected in them, rather than being formed in
newspapers. Newspapers, in other words, were important to spreading nationalism,
but as a reinforcement of things that happened elsewhere. To check the
reasonableness of our findings from topic modelling, we both close read a
significant number of articles and tried to carry out a linguistic analysis of
our corpus.
Sources
Our corpus was of Dutch newspapers in the Dutch national library, accessible via
depher.nl. Based on existing
literature, we decided to study newspapers published in the second half of the
nineteenth century. Not only does existing literature emphasize the importance
of nationalism in the late nineteenth century, but it is also the period when
public debate about Dutch national identity was most strongly polarized [Aerts and te Velde 1999]. We chose 1870 as our start date to avoid the most
serious effects of the national newspaper tax in the Netherlands, which was
abolished in 1869. The tax served to restrict access to newspapers as well as
discourage their publication. Yet over time, average incomes went up, the price
of papers declined and literacy rates went up. After 1870, the Dutch media
landscape became more and more fragmented and journals and newspapers became the
most important vehicles of new views and opinions [van Vree 2000]
[Gunn 1999]. We avoided the problem of inferring mass views from
those of a limited political elite by looking directly at public discourse in
newspapers, as digital tools makes possible on a large scale. Although opinion
is divided about the precise relationship of the public sphere to the newspaper
reporting, the use of newspapers as sources brings with it the promise of being
able to chart public discourse on a scale much larger than existing studies [Broersma 2011]
Studying public discourse in the Netherlands offers a new perspective to a
literature that has been focused on the creation of large nations within Europe:
France, Germany, Italy and the United Kingdom. Although the Dutch nation had
existed as a political or organizational entity for many decades before 1870 –
the first national anthem was chosen in 1815 – a national identity was weak
among the Dutch early on. Privileges like raising taxes, setting rules,
organizing their own political and religious organisations were guarded
jealously by local cities and communities. It was in the nineteenth century that
the liberal elite of the Netherlands came to the conclusion that that
strengthening national identity was a good way to prevent the country from
falling apart into different fractions, as the Catholics and Orthodox
Protestants were making strong claims to their rights as religious communities.
Although neither Catholic nor Protestant elites willingly tried to subvert
national solidarity, the country’s liberal elite felt threatened by each group’s
divergent views of the history of the Netherlands and their claims about the
country’s future. The elite therefore became shepherds of national unity,
campaigning to define and reinforce a Dutch national identity. Central to this
effort was the promotion of royalty: the House of Orange, and especially the
young princess, Wilhelmina, who was crowned on 6 September 1898, a few days
after her eighteenth birthday [Bank and van Buuren 1992, 21–89]
[te Velde 1992]. Niek van Sas argues that the coronation played a
critical role in stimulating national identity in the Netherlands [van Sas 1991, 600].
The newspaper collection of the Dutch National Library is both a rich and a
difficult collection to use. It is rich because of the quantity of digital
titles that it contains, although its coverage is not uniform. In the period
1870-1914, the collection grows from 2500 newspaper issues published in 1870 to
more than 6000 in 1914. While this quantity is helpful for research, mining the
corpus poses three major difficulties. First, the data is messy. The collection
contains a mixture of national, regional and colonial newspapers in the same
dataset, although the metadata generally specifies their area of circulation, so
they can be analysed separately. Second, the quality of the OCR is poor. This
makes it hard to analyse these newspapers using sophisticated techniques that
rely on the semantic information provided by full sentences. Figure 1 shows a
sample from 1880 that epitomizes this problem.
Third, the open source tools available to researchers to mine the collection are
relatively simple. The chief way to access the collection is through the
website. But its search engine only allows researchers to do keyword searches.
In our research, we extensively used the tool known as Texcavator,
developed at Utrecht University in collaboration with the University of
Amsterdam. This tool not only enables more sophisticated searches, but also
allowed us to export search results in bulk for further analysis, such as topic
modelling [van Eijnatten et al. 2014]. The digitization of newspaper
archives is prone to errors and biases that bring a whole range of problems for
digital researchers, which must be must be taken into account by a good
researcher, just as they would be with any other source [Milligan 2013].
Creating A National Community
The late nineteenth century truly seemed to be the age of the nation. It marked
the starting point of four major trends that would come into their own in the
twentieth century: nation building, democratization, bureaucratization and the
rise of the welfare state. At the start of the nineteenth century, there were no
nation states in Europe except France (and perhaps the United Kingdom). Europe
was divided into large empires, some constitutional monarchies and a large
number of small fiefdoms with their own rulers and laws. Slowly, the
nation-state became the central entity in European politics [Mazower 2012, 11]
[Osterhammel 2014, 573–4, 631]. When, mainly in the second
half of the century, the old empires fell and national entities like Germany and
Italy were created, people became citizens of countries with presumably distinct
national identities, united by shared customs, a standardized language and
preferably a national history in which the diversity of the past was neglected
in favour of a story that the national entity now created had always existed on
a cultural level [Maier 2012]. There is no question that the
creation of such states was an artificial process, but how was it achieved?
The Kingdom of the Netherlands was proclaimed in 1813 but lacked any real
national identity. The Dutch Republic of the eighteenth century was a union
based purely on military needs. It was only in times of war that the seven
provinces that made up the Republic deliberated together on strategy and
finance. Outside of wartime, regional and local communities were mostly
self-governing. In 1795, the Batavian Revolution abolished the republic entirely
and created a central state. The revolution declared national unity for the
first time. After an interlude as part of France, the Kingdom of the Netherlands
was proclaimed and inherited this unity. After this, there was a tendency
towards a single national identity, but local identities remained strong and
local customs, laws and regulations were hard to circumvent [Skinner 1989]
[Prak 1999]. Indeed, in the 1830s, the kingdom fell apart into
current-day Belgium, Luxemburg and the Netherlands, and each region faced the
problem of defining a unique national identity. In 1848, the northern region of
the “nation” adopted a liberal constitution and local identities were
slowly forged into a singular national identity. A new field of “national
politics” became the focus of both public and political debates seeking
to define, limit, and challenge the dominant vision of Dutch identity [de Haan 2003]
[de Rooy 2005]. The Dutch nation increasingly became a factor in
the daily life of its citizens, especially in the last quarter of the nineteenth
century, when the national government took on ever more responsibilities for the
wellbeing of its citizens [Wolffram 2003].
The nation’s liberal elite were key actors in the newly active national frame of
the Netherlands. One of their publishing platforms was De
Gids, a leading cultural journal established in 1837. An 1872
article by Charles Boissevain argued that a new reassessment of “public
life” and “national sentiment” was needed in Dutch public discourse.
The author called on his fellows to renew their commitment to defending their
liberal values publicly, as classic liberal ideas on the state, public life and
the nation were under fierce attack from orthodox Protestants and Catholics, who
were actively rewriting Dutch national history to support their disparate
discourses on national identity [Bossevain 1872]
[Raedts 2011, 227–76]. Later historians, like Remieg Aerts,
have demonstrated that articles in De Gids on Dutch
national identity not only grew in number after 1870, but also changed in tone,
especially from the 1880s, as a new nationalist discourse emerged [Aerts 1997, 388–424]. Aerts’ prizewinning thesis is a key
study of Dutch identity in the late nineteenth century, which we used to
contextualize our results.
Limiting A Corpus By Events
The first way that we tried to locate nationalist sentiment in public discourse
was by studying the discourse around events identified in the historical
literature as “nationalist”. Events were useful in our search for relevant
articles because they offered a focus point for public discourse about
nationalism – and a way to translate a complex concept into something that a
computer could find. We used a time period that spanned two years before and
after each event in question. Although we avoided the need to define nationalism
ourselves by drawing on existing literature, the choice of events nevertheless
implicitly defined it. Such events might have been instigated by elites, but
they undoubtedly involved the populace. Because, following Aerts, we expected to
see a change in the tone of Dutch nationalism over time, we compared articles
reporting on a nationalist event in 1872 with articles about an event in 1898.
The first was the commemoration of the landing at Den Briel. The landing at Den
Briel took place in April 1572, so 1872 marked the tercentenary of the invasion
of Den Briel, which was in 1572 under Spanish control - an important turning
point in the Eighty Year’s War. The second event that we used was the
inauguration of Queen Wilhelmina in November 1898.
Topic modelling, the method of analysis that we chose, is a method of text
mining that has been much hyped in recent years [Blei et al. 2003]. It
uses statistics to identify groups of words that frequently occur together.
These groups are known as topics, but have to be identified by the user. The
method is particularly good at identifying groups of related key words in data
that is unstructured and may contain large numbers of transcription errors [Walker et al. 2010]. The key words belonging to each generated
“topic” are “significant” in so far as they are frequently used
together in the corpus. We were interested to see what words were used
frequently together in discourses that we would label, using domain knowledge,
nationalist: topics about nations or national events, the royal house and
potentially words indicating membership in a larger group.
Introducing time – a crucial concern for historians - to topic modelling is an
area of active research, but no group has yet managed to do this in a convincing
way [Wang et al. 2008]
[Qiaozhu and ChengXiang 2005]. We explored the possibility of plotting topic
percentages over time using the time connected to each of our “documents”
or articles, but the result was unconvincing (See Figure 2). Because there was
no better way to see a change over time, we chose events at either end of our
time period. (Although one could argue that these events are not equivalent. See
below.) Choosing to observe historical changes this way introduces a host of
other problems – each event will have different groups of words associated with
each other, for example, and might share no words in common – but we judged
these problems to be outweighed by the importance of looking for changes over
time.
Limiting the corpus of articles modelled has two advantages: first, it makes the
number of articles more manageable, and second, it emphasizes the themes of
interest to historians – particularly in a corpus like ours made up of many
(potentially short) newspaper articles. A key problem with topic modelling is
that most computers are not able to model large numbers of documents containing
a large number of words. This restricts the ability of historians to use this
tool because it forces them to rely on others with larger computers. Using an
undifferentiated corpus, while desirable from a numerical point of view (the
desire to use as many documents as possible to increase the method’s accuracy),
is also problematic because common statistical measures of significance like
tf/idf (topic frequency – inverse document frequency) are not
necessarily useful for inferring historical meaning and may incorrectly
emphasize or deemphasize words in shorter articles, as are typical in a
newspaper [Giffard 2015]. Furthermore, the use of a large,
undifferentiated corpus may lead to the elimination of topics that are of
interest to historians if other topics are discussed more frequently. Because
topic modelling an entire corpus might not allow researchers to explore obscure
topics, researchers should use a more limited corpus. Such a corpus can help
researchers avoid this problem because a limited corpus can be chosen so as to
contain the concept of interest to a degree that is of statistical import.
Defining a smaller corpus also gives the researcher greater control over what
sources are included in it, enabling the researcher to take steps to avoid bias,
for example [Blaxill 2013, 320–1].
We chose to define a sub corpus of articles about each event by using key word
searches in a time period about two years before and two years after the event
in question. To create two corpuses, we used the two search queries:
“(Briel or Brielle) and Nederland*”
and “inhuldiging” [inauguration].[2] To facilitate comparison
between two event sub-corpuses, we chose search terms such that we’d have a
similar number of articles for each time period. The best settings for topic
modelling are hard to define and are different for each case; we used the same
settings for our LDA topic analysis in each case (same number of iterations,
topics, topic size, and same importance threshold) in order to reduce one more
variable from our analysis. These choices could pose additional interpretive
problems because more newspapers – and therefore more articles – came into being
over time (so one would expect more “recent” events to be discussed in a
greater number of articles), but we judged the subset that our search returned
to be representative. In all of our tests, we relied on the existing metadata in
the national collection to define newspapers with “national” or
“regional” circulation as well as “articles” rather than
“advertisements”. For each event corpus, we modelled the content of the
article including its title, but removed other metadata such as the title of the
newspaper. The results are given below:
Search | Dates | Articles | Nationalist Topic Produced |
“(Briel or Brielle) and Nederland*” | 01.01.1870 to 31.12.1874 | 3,462 articles (1.79 million words) | Vereeninging des feest koning Nederland leden warden twee oranje briel eene heeren waar uur prins[3] |
“Inhuldiging” | 01.01.1896 to 31.12.1901 | 2,330 articles (1.5 million words) | Koningin volk oranje majesteit groote waar willem moeder uwe onze waarop prins gouden Wilhelmina allen[4] |
Because the two events we chose are not equivalent, we were surprised to see
similar language used in the topics for both events, and thus words used in the
articles mentioning these events. The first event split opinion particularly
among Catholic and Protestant communities who were divided on whether the people
who landed at Den Briel were heroes or not, whereas the second event was framed
mainly by the liberal political elite to reemphasize national unity and reaffirm
tolerance as the core of Dutch national identity by stressing the people’s
ability to cope with societal and religious differences.
The similarity in language supports the argument, made by Frans Groot, that
newspapers sought to pacify conflicts and differences by using a more neutral
vocabulary [Groot 1995]. Seeing similar language used a quarter of
a century later to describe the coronation of the new Dutch queen suggests that
the newspapers adopted a similarly understated stance to later nationalistic
events. This result suggested that we could be confident that including articles
over a longer time period in our topic modelling would not compromise
meaning.
Topic Models Over a Longer Time Period
Studying nationalism using a corpus covering a longer time period required us to
find a different way of limiting our corpus than by events. Tracing a concept is
naturally more complicated than following the use of a word over time, and
finding a non-event based corpuses was similarly more complicated. We wanted to
avoid defining “nationalism” too strictly in order to let the sources
speak, so we looked for quasi-objective keywords to limit our corpus. Literature
on Dutch nationalism tells us that the terms “vaderland”, “volk”, and “natie”
did not change much in meaning over the last quarter of the nineteenth century
[Aerts and te Velde 1999]. So we adopted these words as search terms. We
began by creating a “nationalist” sub-corpus defined by articles containing
the keyword “vaderland” in national
newspapers published from 01 January 1880 to 01 January 1900.
To see that the selection focused our search, we compared this sub-corpus to one
generated using a keyword that did not have to do with nationalism according to
the literature. For the more general sub-corpus, we sought a corpus of similar
size (in articles) to the “vaderland”-corpus. Our selection (we tried
search words like “cow”, “boat”, “rain” and “tree” that
might reflect frequent Dutch concerns, the number of articles returned for each
is shown in Table 2.) fell eventually on “bier” [beer]. As we discovered, the Dutch word “bier”
was often incorrectly OCR’d as the Dutch word “hier” [here], thus adding
numerous articles to the corpus that did not actually have to do with beer. This
was judged to be an acceptable mix-up in this case because we were searching for
a general corpus rather than specific information about beer.
Sub-corpus defined by search term | Articles |
vaderland (fatherland) | 28,807 |
koe (cow) | 122 |
boot (boat) | 18,609 |
kaas (cheese) | 20,764 |
Regen (rain) | 21,479 |
Bier (beer) | 26,449 |
Vrouw (woman) | 58,385 |
Using the two sub-corpuses thus created (“vaderland” and “bier”), we were able to begin our search for nationalist
sentiment. We began by doing collocation analysis on the two sub-corpuses. We
found that the “vaderland”-corpus uses the
word "ons" [our] within three words to the left
of “vaderland” 7,386 times; it uses the
word “vaderland” 36,791 times. So about
21% of the occurrences of “vaderland” in
the “vaderland”-corpus are connected to
ons. The “bier”-corpus, in contrast, uses
“ons” up to three words before
“vaderland” 370 times compared with
2,003 occurrences of the word “vaderland”,
or 19% of the time.
Bier | Vaderland | |
“Vaderland” | 2,003 | 36,791 |
“Ons…. Vaderland” | 370 (19%) | 7,386 (21%) |
“Volk” | 6,259 | 20,901 |
“Ons…. Volk” | 484 (8%) | 2,463 (12%) |
These findings suggests that using the sub-corpus did indeed allow us to focus
our search on a “nationalist” theme, because the absolute number of times
the word “vaderland” appears is much
greater than in the more general “bier”-corpus. Nevertheless, while the statistics suggest that
the nationalist theme (represented by these words) was more present in the
“vaderland”-corpus, we can also see by
the similar percentages for the appearance of “ons” and “vaderland”
that the sub-corpus did not over-represent, percentage-wise, nationalist themes.
Limiting the corpus in this way did not mean that we expected only nationalist
themes to emerge from the nationalism-sub-corpus (not least due to OCR errors);
just that we expected nationalism to be a key theme among those discussed in the
articles chosen – and indeed it appears to be.
We then sought to test our corpuses for the influence of time. In order to do
this, we created additional limited corpuses that covered the years from 1875 –
1880 (early) and 1895-1900 (late). In comparing early to late, we saw no great
increase in the use of the modifier “ons”
before either “vaderland” or “volk” in either corpus. This suggests that
nationalism was persistent in Dutch newspaper articles between 1875 and 1900 but
low-level. Table 4 gives a summary of the results.
Bier | Vaderland | |||
Early | Late | Early | Late | |
Articles | 2,877 | 16,841 | 6,118 | 11,332 |
“Vaderland” | 399 | 1,008 | 8,100 | 14,172 |
“Ons… vaderland” | 94 (24%) | 155 (15%) | 1,522 (19%) | 2,526 (18%) |
“Volk” | 926 | 3,662 | 3,772 | 8,251 |
“Ons… volk” | 60 (7%) | 273 (8%) | 405 (11%) | 772 (9%) |
We next applied topic modelling to both the “vaderland”- and “bier”-sub-corpuses. We modelled the corpus connected to
each event in two ways: firstly, treating each article as a single document and
secondly, treating each paragraph as a single document, reasoning that
paragraphs would be defined by coherent themes. Interestingly, the first
produced more interpretable results, justifying our decision to choose our
corpus based on numbers of articles.
After applying topic modelling to both corpuses, we used our domain knowledge
based on existing literature to classify the topics. Looking at the topics
produced by the language-indepdendent Mallet GUI, we found that both
sub-corpuses had topics in common. We took this as evidence that the topics were
of importance in Dutch newspapers generally, rather than just in our “vaderland”-corpus. But what we saw on
comparing the topics generated for each corpus, like the Boerwar topic shown in
Table 5, was that the corpuses used different language to discuss the same
topics. Again, limiting the corpus did not mean that we expected nationalism to
be the only topic discussed in these articles. We expected “nationalism” to
be present in the sub-corpus, guaranteeing that we could find it, but not making
it the only theme. The bold words are unique to each corpus.
Topic | “Vaderland”-corpus | “Bier”-corpus |
Boerwar (1899-1902) | Engeland zuid engelsche afrika boeren Transvaal land the engelschen amerika oorlog republiek president londen britsche groote hen lord Holland zullen[5] | General oorlog boeren zuid afrika troepen man president Transvaal brief warden colonel dag twee Pretoria leger ontvangen vijand berichten telegram[6] |
Trade | Land handel Nederland onze landbouw groote nijverheid nederlandsche zeer belang duitschland industrie waar thans landen vaderland buitenland groot werk alle[7] | Nederland handel bier land artikelen firma waarde landen alle enz goederen nederlandsche invoer gebruik industrie jaar groote landbouw welke engeland[8] |
The first topic shown in Table 5 shows that the Boerwar (1899-1902) was important
in both corpuses. Yet the language used to describe the war was clearly
different in the two sub-corpuses: the first focused more on “ethnic”
descriptors rather than the more “news”-like words of the second corpus.
The second topic we chose was trade, another important theme with regard to the
Netherlands. In the “vaderland”-corpus, we
found that the topic was expressed using “national” terms – particularly
referring to foreign nations, which we would expect to see in a world beginning
to organize itself by nation-states [Anderson 1983, 95–8].
The most similar topic in the “bier”-corpus, in contrast, uses more general words. It was
interesting that the two corpuses had unique vocabularies for discussing
similarly important events. This too suggests that nationalism in newspapers was
expressed through the constant presence of more banal mechanisms that suggest a
larger change in how the world was organised and understood. Although the
“vaderland” corpus was thus more
concerned with nations than the more general “bier” corpus, we did not see any emotional, nationalist
rhetoric.
Linguistic Analysis
Our topic modelling suggested that larger historical changes were reflected in
newspapers not through the presence of emotional rhetoric, but in the use of a
vocabulary that changed over time. Indeed, many authors have pointed to
linguistic changes, such as the increasing use of the term “national” or
references to national organizations, that indicate the growth of national
identity, so we tried to use these changes to track the process of national
identity building in Dutch newspapers. Seeing an increase of such changes over
time would indicate increasing intensity of personal association with a national
grouping, in this case the Netherlands, as opposed to local groupings, such as
the Dutch provinces. Although our attempts at linguistic analysis were
suggestive but ultimately unsuccessful, we will shortly describe the major tests
that we carried out and the problems that we faced in trying to come to
conclusive answers.
Firstly, we used ngrams to track the usage of keywords that refer to nation
states over time. The frequency of words like “Nederland” [the Netherlands], but also “Tweede Kamer” [the Dutch parliament], “Premier” [prime minister], “nationaal” [national], “vaderland” [fatherland], and “Nederlands” [Dutch] did indeed rise over the nineteenth
century. We hoped to be able to compare this increasing usage with the number of
references made to local organizational forms, since we would expect local
organizational forms to be replaced by national ones. Words that refer to local
communities, however, like the names of the different Dutch provinces, hardly
decreased over the period in question (See Figure 3).
Although trying to search for these words did not yield the results we hoped for,
it suggested that we might find something if we compared word usage in
newspapers with local as opposed to national circulation. The results were
disappointing, however. The term “provincie” [province] for instance appears almost as
frequently in national as regional newspapers. Between 1870 and 1914, the term
“provincie” appears 85,583 times in
national papers and 112,307 in regional papers – but more regional newspapers
have been digitized and this number is constantly changing, one reason why using
a limited sub-corpus gives the researcher more control. It would perhaps be more
fruitful to examine how many newspaper column inches were devoted to national as
opposed to regional news or discourse, but that relies on being able to use a
computer to distinguish between national and regional news. Ultimately, however,
although a graph of linguistic use over time seems to suggest an increase in
reference to national units, this is difficult to translate into information
about personal identity as opposed to just bureaucratic organisation. That the
national should be increasingly referred to was not unexpected given that
citizens would be expected to increasingly have intercourse with national
organizations as these are established. These results, while suggestive, show
the difficulty of translating historical questions into questions that can be
answered using digital methods – or conversely, of limiting our historical
questions to questions that can be answered using digital methods.
Despite approaching mining newspapers from many different angles, none of our
experiments turned up evidence of emotional, nationalist rhetoric in Dutch
newspapers in the last quarter of the nineteenth century. Instead, we saw
indications that nationalism was spread through much more quotidian methods. So,
following Billig, we looked particularly at the use of pronouns in newspaper
articles. Because such subtle expressions of nationalism would be expected to
occur in any and all types of article – whether about national politics, sports
or the weather – our examination used the whole corpus (so all articles for the
time period under study). But subtle changes such as the references of pronouns
are difficult to mine for. It is easy to see that the number of articles that
contain both the word “Nederland”
[Netherlands] and the pronoun “wij” [we]
was on the rise in the nineteenth century, for example (See Figure 4). Also, one
finds that nationalist word combinations like Billig’s “ons land” [our land] were used more frequently in 1900
than 1870 (See Figure 5). Like the previous linguistic tests, the graphs given
in Figures 4 and 5 suggest an intensification of identification with the
nation-state over time. Unfortunately, to be able to really assess whether the
use of pronouns changes over this period, we would need to be able to determine
the exact correlation between noun and pronoun.
Examining the linguistic structure of a large amount of messy data poses
fundamental technical difficulties – even when the OCR quality of the corpus is
perfect, which was not true in our case. For the same reason – the lack of
semantic information in our corpus (i.e. the guarantee that contiguous words are
correctly transcribed in a large proportion of instances) – we were unable to
use sentiment mining as a tool in our research, although it would have shed
important light on some aspects of the “nationalism” question, such as
whether individual newspapers viewed the nation positively or negatively at
different points in time. In so far as linguistic changes are signals of wider
historical changes, we want to be able to find them on a large scale, but we
need this to be theorized by historians as well as by linguists and
sociologists. It remains an open question about the potential of such analysis
in a collection of nineteenth century newspapers such as we used in our study.
An important part of the source criticism that we wanted to do for digital searches
in our data is to measure or estimate the level of error or uncertainty (and
conversely certainty) that accompanies each search. We hardly expect the results
to be 100 per cent accurate (given the tendency to false positives as well as
false negatives), but some levels of error are acceptable for our research,
while others are too high. Not knowing even the order of magnitude is a serious
stumbling block [Traub et al., n.d.][Milligan 2013]. We
recognize that errors are generated as much from computational quirks as from
digitization, and studying the errors of these methods will undoubtedly benefit
from the input of trained statisticians. Until this occurs, it will be difficult
to use such tools for anything more than suggestive research.
Conclusion and Outlook
The experiments described in this paper focused on finding evidence of
nationalism, a complex topic that is common in the professional, historical
literature. Our study of newspapers in a small, European country was
particularly important because the secondary literature claims that they were
very important for spreading nationalism in the late nineteenth century. We
first tested whether the nationalist language present in newspapers was more of
an emotional or banal sort, thereby testing existing hypotheses about how ideas
about national belonging reached the public via newspapers. We used digital
methods to interrogate our sources because they allowed us to analyse large
corpuses of newspaper articles quickly. What we found — not in elite publications
but through a much broader analysis of thousands of newspaper articles and
millions of words made possible by digital tools — suggests that the majority of
the Dutch population would have been exposed to nationalist thinking through
subtle expressions of national belonging rather than emotional rhetoric.
Although our findings are not by any means conclusive, they do demonstrate that
inferring general views about nationalism from discourse in elite publications
is problematic.
Although Michael Billig used a present-day perspective in his book and based his
arguments about banal nationalism mostly on sociological literature, we found
that his work establishes a useful conceptual framework in which we can
understand different forms and expressions of nationalism in the public media.
With regard to Dutch nationalism in particular, our findings also support and
extend the argument of Van Sas. The problem, as critics of the linguistic turn
in history have pointed out, is that observing a change in language in
newspapers does not allow us to make a claim about causality or who the actors
were who were driving a given process. Indeed, our study indicates that we need
to take seriously the possibility that Western Europe’s experience with
nationalism in the twentieth-century has caused historians to look for (and
highlight) similarly inflamed rhetoric in earlier periods, when such passionate
appeals may have been rare rather than representative.
Through applying digital methods to test a hypothesis found in the historical
literature, this paper has contributed to both the study of nationalism and the
development of digital methods for concept mining. Although our use of digital
methods let us analyse many more sources than is traditional in nationalism
studies, thereby enriching the field, we found that major methodological
development — not to mention theorisation — is still necessary to apply existing
tools to our problem. We found it both necessary and desirable to use smaller
corpuses of sources to answer targeted questions, using computers as both search
tools and tools of analysis. Using a limited sub-corpus may make it harder to
use digital analysis techniques that require training computers using large
numbers of documents, but not doing so risks that less popular themes will be
drowned out by other discourses. Using a sub-corpus, as others have done [Blaxill 2013], also increases a researcher’s ability to describe
the corpus and thus to carry out source criticism.
Unsurprisingly, creating a valid and useful sub-corpus requires composing a good
search query. What this is depends on the research question. In this case, in
order to study public discourse, we looked for neutral search terms (terms that
the literature has concluded were neutral) over the time period that we wanted
to study. While we chose terms that would point to events or topics that were
publicly visible, thus providing both an opportunity and a reason for public
discourse about national identity, we were careful not to choose terms that were
themselves charged with meaning or possessed a changing meaning over the time
period that we studied. We used multiple methods in order to check the
plausibility of results from particular methods. Nevertheless, we found, as
others have suggested, that external domain knowledge was indeed crucial in
interpreting our results in each step of the process. The desire to use existing
digital tools to answer our research question forced us to think about
nationalism in many different ways, including especially how it was manifested
linguistically, although OCR errors in our nineteenth century newspaper corpus
made analytical methods that relied on semantic information inconclusive. We
need to be careful, however, because reliance on digital methods can result in
elevating certain types of meaning and tests that we as historians are not
perhaps competent at using or that we would not otherwise rely on. We found, as
others have, that seeking to test existing hypotheses produced interesting leads
for further investigation (probably using traditional historical
methods — although we did not want to rely on close reading, we did end up close
reading some 400 articles to check that our results were not absurd, since the
methods that we used are still being developed).
With its successes and failures, this project represents an important step
towards developing a method to mine public discourse from public media – both
the content of and the degree of public support for particular debates over
time. We will continue to explore how we can answer questions about identity
formation using digital methods to analyse large repositories of historical
documents. Developing our ideas further will require developing new, advanced
methods for analysis as well as for corpus selection. Yet we have already seen
that each and every digital output must be subjected to historical
interpretation. Using digital methods is messy, but so is all historical
research.
Notes
[1] Article about a celebration
on board a Dutch ship.
[2] The
asterisk is a multiple character wildcard search that returns matches with 0
or more additional characters. The search “Nederland*” would thus also
return “Nederlanders” and “Nederlandisch” as well as words with the
given stem but OCR errors in the ending like “Nederlandens”.
[3] union the party king Netherlands members values
two orange Briel one misters were hour prince
[4] queen people orange majesty big where Willem
mother your our when prince gold Wilhelmina all
[5] England south
English Africa farmers Transvaal country the English America war
republic president London British large the lord Holland
shall
[6] general war farmers south Africa troops person
president Transvaal letter wards colonel day two Pretoria army
received enemy messages telegram
[7]
country trade Netherlands our agriculture large hard-working Dutch
very importance Germany industry where now countries fatherland
foreign-country large work all
[8] Netherlands trade beer country articles
company worth countries all etc. goods Dutch import use industry
year large agriculture which England
Works Cited
Aerts 1997 Aerts, Remieg. 1997. De Letterheren. Liberale cultuur in de
negentiende eeuw: het tijdschrift De Gids.
Amsterdam.
Aerts and te Velde 1999 Aerts, Remieg and Henk te
Velde. 1999. “De taal van het
nationaal besef, 1848-1940.” In Vaderland. Een geschiedenis vanaf de vijftiende
eeuw tot 1940, edited by N.C.F. van Sas, 391-454.
Amsterdam.
Anderson 1983 Anderson, Benedict. 1983. Imagined communities. London.
Bank and van Buuren 1992 Bank, J. and M. van Buuren.
1992. 1900. Hoogtij van burgerlijke
cultuur. Den Haag.
Baycroft 2004 Baycroft, Timothy. 2004. French Flanders in the Nineteenth and Twentieth
Century. Rochester.
Billig 1995 Billig, Michael. 1995. Banal Nationalism. London.
Blaxill 2013 Blaxill, Luke. “Quantifying the Language of British Politics, 1880–1910.”
Historical Research 86.232 (2013): 313–41.
Blei et al. 2003 Blei, David, A.Y. Ng and M.I.
Jordan. 2003. “Latent Dirichlet Allocation. ”
Journal of Machine Learning Research 3:
933-1022.
Bossevain 1872 Bossevain, Charles. 1872. “Iets over de tentoonstelling in
Arti.”
De Gids 36:
529-562
Breuilly 2012 Breuilly, John. 2012. “What does it Mean to Say that Nationalism is
‘Popular’?” In Nationhood from below. Europe in
the Long Nineteenth Century, edited by Maarten van Ginderachten and
Marnix Beyen, 23-43. Basingstoke.
Broersma 2011 Broersma, Marcel. 2011. “Nooit meer bladeren? Digitale
krantenarchieven als bron.”
Tijdschrift voor Mediageschiedenis 14.2: 29-55.
Clark 2013 Clark, Christopher. 2013. The Sleepwalkers. How Europe Went to War in 1914.
London.
Edensor 2002 Edensor, Tim. 2002. National Identity, Popular Culture and Everyday Life.
Oxford.
Gellner 2008 Gellner, Ernest. 2008. Nations and Nationalism Ithaca, NY.
Giffard 2015 Giffard, Hermione. 2015. “Mining Newspapers. A Plea for Significance.” Beyond
Methods of Mining, Utrecht, 14-15 September 2015. Conference report:
asymenc.eu.
Groot 1995 Groot, Frans. 1995. “De strijd rond Alva's bril. Papen en geuzen bij
de herdenking van de inname van Den Briel, 1572-1872. ”
BMGN–Low Countries Historical Review 110.2:
161-181.
Gunn 1999 Gunn, S. 1999. “The
public sphere, modernity and consumption: new perspectives on the history of
the English middle class. ”In Gender, civic
culture and consumerism: Middle class identity in Britain 1800-1914,
edited by A. Kidd en D. Nichols, 12-29. Manchester.
Hobsbawm 2012 Hobsbawm, Eric J.. 2012 [1990].
Nations and Nationalism Since 1780: Programme, Myth,
Reality. Cambridge University Press: Cambridge.
Lodge 1993 Lodge, A.R. 1993. French: from Dialect to Standard. London.
Maier 2012 Maier, Charles S.. 2012. “Leviathan 2.0: Inventing Modern Statehood. ”In A World Connecting, 1870-1945, edited by Emily
Rosenberg, 29-282. Cambridge, MA.
Mazower 2012 Mazower, Mark. 2012. Governing the World. The History of an Idea.
London.
Milligan 2013 Milligan, Ian. 2013. “Illusionary Order: Online Databases, Optical Character
Recognition, and Canadian History, 1997-2010. ”
The Canadian History Review. 94.4: 540-569.
Osterhammel 2014 Osterhammel, J. 2014. The Transformation of the World. A Global History of the
Nineteenth Century. Princeton.
Prak 1999 Prak, Maarten. 1999. Republikeinse veelheid, democratisch enkelvoud.
Sociale veranderingen in het revolutietijdvak, ’s-Hertogenbosch
1770-1820. Nijmegen.
Qiaozhu and ChengXiang 2005 Qiaozhu M. and Z.
ChengXiang. 2005. “Discovering evolutionary theme patterns
from text: an exploration of temporal text mining. ”In Proceedings of the eleventh ACM SIGKDD international
conference on Knowledge discovery in data mining, 198-207.
Raedts 2011 Raedts, Peter. 2011. De ontdekking van de Middeleeuwen.
Geschiedenis van een illusie. Amsterdam.
Renan 1992 Renan, Ernest. 1992. Qu’est qu’une nation? Et autres essais
politiques, texts chosen and presented by Joël Roman.
Paris.
Skey 2009 Skey, Michael. 2009. “The national in everyday life: A critical engagement with Michael Billing’s
thesis of Banal Nationalism. ”
The Sociological Review 57: 331-346.
Skinner 1989 Skinner, Q.. 1989. “The State. ”In Political
Innovation and Conceptual Change, edited by T. Ball, J. Farr and
R.L. Hanson, 90-132. Cambridge.
Traub et al., n.d. Traub, Myriam C., Jacco van
Ossenbruggen, and Lynda Hardman. “Impact Analysis of OCR
Quality on Research Tasks in Digital Archives”, n.d.
Walker et al. 2010 Walker, Daniel D., William B.
Lund and Eric K. Ringger. 2010. “Evaluating Models of Latent
Document Semantics in the Presence of OCR Errors. ”In Proceedings of the 2010 Conference on Empirical Methods in
Natural Language Processing, 240–50.
Wang et al. 2008 Wang, Chong, David Blei, and David
Heckerman. 2008. “Continuous Time Dynamic Topic Models.
”In Proceedings of the Twenty-Fourth Conference
Annual Conference on Uncertainty in Artificial Intelligence
(UAI-08), 579-586.
Wolffram 2003 Wolffram, D.J. 2003. Vrij van wat neerdrukt en beklemt.
Staat, gemeenschap en sociale politiek, 1870-1918.
Amsterdam.
de Haan 2003 de Haan, Ido. 2003. Het beginsel van leven en wasdom. De
constitutie van de Nederlandse politiek in de negentiende
eeuw. Amsterdam.
de Rooy 2005 de Rooy, Piet. 2005. Republiek van rivaliteiten. Nederland
sinds 1813. Amsterdam.
te Velde 1992 te Velde, H. 1992. Gemeenschapszin en plichtsbesef.
Liberalisme en nationalisme in Nederland, 1870-1914.
Den Haag.
van Eijnatten et al. 2013 van Eijnatten,
Joris, Toine Pieters and Jaap Verheul. 2013. “Big Data for
Global History. The Transformative Promise of Digital Humanities. ”
BMGN - Low Countries Historical Review 128.4:
55-77.
van Eijnatten et al. 2014 van Eijnatten,
Joris, Toine Pieters and Jaap Verheul. 2014. “TS Tools:
Using Texcavator to map public discourse.”
Tijdschrift voor
Tijdschriftstudies
35: 59-65.
van Sas 1991 van Sas, Niek. 1991. “Fin-de-Siècle Als Nieuw Begin.
Nationalisme in Nederland Rond 1900.”
BMGN - Low Countries Historical Review 106.4:
595-609.
van Sas 2004 van Sas, Niek. 2004. De metamorfose van Nederland. Van oude
orde naar moderniteit, 1795-1900. Amsterdam.
van Vree 2000 van Vree, Frank. 2000. De politiek van de openbaarheid.
Journalistiek en de publieke sfeer. Groningen.