Abstract
This article examines the potential of employing structured texts, encoded in the
Parliamentary Metadata Language XML schema, for the machine-readable analysis of
substantial corpora of legislative proceedings. It demonstrates the potential of
using PML corpora for combining the results of sentiment analysis with
contextual metadata to establish and visualise patterns of divergent attitudes
towards a topic such as immigration as they correlate with such features as
party affiliation or geographic location. This is readily achieved using such
simple techniques as XSLT transformations or XQUERY searches.
Introduction
Large-scale digitisation projects in many countries over the last twenty years
have generated significant machine-readable textual corpora of the proceedings
of their parliaments or legislative assemblies. In the United Kingdom, for
instance, a number of projects have enabled seven hundred years of records to be
made available in digital form, including the full text of the official Hansard
record of debates from 1803 [
UK Parliament 2012]. These corpora are
potentially highly significant resources for large-scale machine-based analysis,
although at present studies of this type are rendered more difficult by the
heterogeneity of approaches to markup and encoding taken by the projects that
created them.
In recent years, a number of projects have attempted to address the issues raised
by this heterogeneity and formalise schemes for rationalising approaches to the
encoding of these texts and their associated metadata. In Portugal, for
instance, Dublin Core (DC) is used as the basis for a digital library of
parliamentary records [
Pinto et al. 2005] and in Chile the National
Library has produced an extended DC element set to act as the underlying
descriptive metadata for its digitisation programme [
Fuentes Martínez 2005]. A more ambitious approach has been
undertaken by the Akomo Ntoso project for African legislative, parliamentary and
judiciary documents [
Cervone et al. 2015] which has created a formal XML
schema and controlled vocabularies.
More recently, the LIPARM (Linking the Parliamentary Record through Metadata)
project [
Gartner 2012] attempted to define a more
sophisticated methodology for parliamentary metadata by devising an XML schema,
PML (Parliamentary Metadata Language) [
Gartner 2013] that is
intended to provide a means of semantically linking core facets of legislative
proceedings into a single coherent framework. The schema was intended primarily
as a resource discovery tool, allowing a diverse range of previously
incompatible digitised resources to be conjoined using common semantic linkages
and so become interoperable at a search level. The schema was tested on a corpus
of UK Parliamentary materials and proved itself capable of allowing
sophisticated searching and browsing of parliamentary records in a prototype
interface to PML records constructed for the project [
Gartner 2013, 32].
These approaches are primarily aimed at resource discovery rather than the
analysis of the textual content of proceedings of the type that has become
established in fields such as corpus linguistics. Such studies have been
relatively rare in the past: until the last five years, most historical research
on parliamentary proceedings has tended to take the form of qualitative analyses
based on manual readings. There appears to be have been considerable suspicion
of corpus-driven analyses of political vocabulary in particular; some argue that
this stems from a prevalent post-structuralist emphasis in the historical
community on the micro reading of texts rather than the analysis of broad trends
[
Blaxill 2014].
Despite these suspicions, more quantitative approaches have begun to emerge in
recent years, the most sophisticated of which have been those conducted in the
Netherlands using the Political Mashups schema, a TEI extension which is based
on the latter's elements sets for theatrical performance [
Gielissen and Marx 2009, 19]. This has been used, for instance, to
examine attitudes expressed in the country’s parliamentary proceedings over a
lengthy time period towards a well-known party of the far-right [
Piersma et al. 2014].
Although not designed primarily as an analytical tool, the semantic linkages
encoded within a PML file, when used in conjunction with the texts whose
contents they synthesise, clearly offer the potential for moving beyond resource
discovery alone towards something more analytical. Instead of merely allowing
these texts to be found, it should allow them to become the raw material for
machine-based analyses, using the mechanisms associated with a discipline such
as corpus linguistics. The corpora on which this field of study relies integrate
texts with metadata, usually the syntactical information associated with each of
their constituent words. In a similar way, PML integrates data and metadata and
so should be able to facilitate analyses of the same type.
This paper aims to demonstrate how PML can be used in this way; by analysing the
content of parliamentary proceedings and using its associated metadata to put
the results of these analyses into context, it becomes possible to generate
correlations revealing high-level patterns within these texts. In this study,
the tools used for this are relatively simple. Sentiment analysis tools are used
on a small corpus of materials encoded in a slightly extended version of the PML
schema and nothing more sophisticated than basic XSLT (eXtensible Stylesheet
Language Transformation) stylesheets are employed to create visualisations and
analyses based on the output of these tools.
The aim is to demonstrate that, even with these simple techniques, sophisticated
and revealing results can readily be obtained from a PML corpus. Extensive
synchronic and diachronic studies across substantial datasets are achieveable
with these techniques which add a layer of context to the results of standard
tools for analysing textual corpora; this additional layer has the potential
significantly to enrich these studies, particularly by enabling correlations
between the purely linguistic and the contextual to be investigated with
relative ease.
Parliamentary Metadata Language (PML)
The Parliamentary Metadata Language (PML) schema [
LIPARM Project 2012] was originally devised as the key component of the LIPARM project mentioned
above. It was conceived as a rigidly structured framework, encoded in XML
syntax, for semantically linking core facets of records of legislative
proceedings. Seven such facets are incorporated into the schema, most of which
are defined very broadly and at a high level of abstraction: they include such
concepts as
Unit (covering everything from
political parties, chambers of the legislature, parliamentary constituencies and
even gender) and
Proceedings Object (covering
everything that occurs within the proceedings themselves, from procedures such
as prayers to speeches and other contributions by individual members). The
semantic breadth of most of these facets requires them to be narrowed in use by
employing controlled vocabularies of sub-facets — for instance,
Units are refined by these vocabularies into type of
unit. A fuller description of the architecture of PML may be found in [
Gartner 2013].
PML is designed to act as integrative mechanism for parliamentary proceedings,
allowing their textual content to be conjoined with structured metadata: in
doing so, it allows diverse content of this kind to be linked into a coherent
and interoperable whole. It acts in this way as an “intermediary schema”
[
Gartner 2011], a mediator between resources that would otherwise be difficult to treat
as an integrated resource. The primary mechanism to achieve this is an element
available to most facets within a PML document: this
<source> element,
contains an attribute
@sourceRef which allows a link to an external
resource via such mechanisms as URI, Xlink or Xpointer. A speech in a
parliamentary debate might, for instance, be linked to its text in a digitised
version of
Hansard as follows:
<contribution
type="speech"
typeURI="http://liparm.ac.uk/contributions/speech"
contributorID="hh-1980015-person0002">
<label>Speech</label>
<sources>
<source sourceRef="http://hansard.com/commons/1980/jan/15/e-comm-act-amendment#column_1436" sourceType="URL">
<label>HC Deb 15 January 1980 vol 976 cc1436-41</label>
</source>
</sources>
</contribution>
Example 1.
Sample PML contribution element (from [
Gartner 2013, 29] (truncated))
This example also demonstrates the mechanism by which the broad element
<contribution> is narrowed semantically to a type of contribution
(here a speech) by the use of the @typeURI attribute, the use of a
<contributorID> element to indicate the identity of the member giving
the speech and the use of <label> elements to provide human-readable
handles for each component.
As originally conceived in the LIPARM project, PML was intended primarily as a
resource-discovery mechanism, allowing the diversely-encoded set of digitized UK
parliamentary proceedings to be integrated semantically at a fine level of
granularity. For this reason, the PML architecture did not itself incorporate
the textual content of the proceedings themselves within its element set:
instead, the
@sourceRef attribute established linkages to this
content. This method was employed in the experimental interface to PML data
constructed for the LIPARM project [
LIPARM Project 2012]: this
linked PML files to simple HTML renderings of the original text.
The rich set of semantic linkages made possible by the LIPARM architecture
should, however, prove amenable to more sophisticated uses than resource
discovery alone. It can also be used to support and enrich analyses of the type
which are in common usage in the fields of corpus linguistics. In particular,
this network of linkages has the potential to put the results of linguistic
analyses in context by relating them to the rich set of facets encoded within
the PML architecture and, via semantic linkages, to external metadata. The next
sections of this article discuss how this can be done using such simple tools as
XSLT transformations or XQUERY searches.
Creating a PML corpus
To demonstrate the capabilities of PML, a corpus of encoded files was created
that covers the period of the last parliament in the UK (2010-2015). This
corpus, part of a larger collection covering seventy years of UK parliamentary
proceedings, was generated by integrating data from a number of sources: most of
the texts themselves were derived from a set of files encoded in the Political
Mashups XML schema, which were themselves parsed from the HTML files generated
by the Hansard project mentioned above. Other data came from the controlled
vocabularies encoded in MADS (Metadata Authority Description Schema) which were
produced by the LIPARM project: these included data on Members of Parliament and
geographical constituencies. Three consecutive XSLT transformations collected
this data from these diverse sources (12,086 files in all) and integrated them
into a series of PML files, one covering each day of proceedings.
A minor amendment was made to the PML schema to facilitate its use as the basis
for an analytical corpus. The
@sourceRef attribute discussed above was
supplemented by the addition of a new element under its parent
<source>
to allow the text of the proceedings to be incorporated directly into the PML
file. This
<content> element is used here to include the text of a
member’s contribution to a debate:
<contribution typeURI="http://liparm.ac.uk/id/contributions/speech"
type="speech"
contributorID="hh-1980015-person0002"
regURI="http://uk.proc.d.2010-03-04.2.2.2">
<label>Kevin Brennan</label>
<sources>
<source>
<content>
<p>On 2 July 2009 the Government published the consumer White Paper, which details plans for more effective enforcement against those who deliberately set out to defraud consumers. I recently announced funding of £4.3 million for the Office of Fair Trading and trading standards to tackle those who use the internet to con consumers.</p>
</content>
</source>
</sources>
</contribution>
Example 2.
Sample contribution record with text of contribution
included in
<content> element
Although the <content> element in this example contains simple <p>
(paragraph) elements only, XML data conforming to any namespace would be valid
here.
The addition of this element allows XML-encoded text of any degree of complexity
to be integrated within the heavily structured metadata architecture of PML in
a manner analogous to the integrated text and metadata used in many e-text
projects. Integrating the text in this way is, of course, not strictly necessary
to perform the type of analysis discussed in this article: the linkages
established by the @sourceRef attribute would allow the disparate
corpora of PML and text files readily to be treated as a single entity. The XSLT
and XQUERY mechanisms by which the corpora may be interrogated will work just as
effectively on such a distributed corpus.
Applying sentiment analysis to the PML corpus
To test the feasibility of using PML as an analytical tool, simple sentiment
analysis was carried out on a portion of the corpus that covered a single topic,
attitudes to immigration. Like all sentiment analysis, this attempted to discern
the perspective or attitude of the speaker but was limited to a basic
categorization of their expressed views in terms of polarity, whether they were
positive, negative or neutral. It did not try to discern more complicated
sentiments such as emotional moods or states.
This sub-corpus was generated by a simple XQUERY search to extract members'
contributions during this period in which the stems
immig* or
migr* were present. This sub-corpus was then run through the
OpinionFinder sentiment analysis software [
MPQA Project n.d.] to tag these contributions for positive, negative or
neutral sentiments within the same paragraph as the search terms.
OpinionFinder is a Java-based application devised by
the Universities of Pittsburgh, Cornell and Utah. It can rapidly process
multiple files to identify subjective linguistic elements which are then
automatically tagged using inline SGML elements [
Wilson et al. 2005]. A
paragraph element from a PML file tagged in this way might appear in this
(slightly simplified) form:
<p>Immigration has <MPQAPOL autoclass="positive">enriched</MPQAPOL> our culture and <MPQAPOL autoclass="positive">enhanced</MPQAPOL> our society. Britain can benefit from immigration, but not <MPQAPOL autoclass="negative">uncontrolled</MPQAPOL> immigration. The levels of net migration seen under the previous Government-an annual figure of almost a quarter of a million at its peak in 2004-were <MPQAPOL autoclass="negative">unprecedented</MPQAPOL> in recent times. </p>
Example 3.
sample OpinionFinder output (simplified)
For the illustrative purposes of this article, these tags were used to generate a
basic measure of the degree of positive or negative sentiment per paragraph by
counting the relative numbers of positive, neutral and negative sentiments
marked. Clearly more sophisticated techniques are available for analysing output
of this type, but these simple measures are sufficient to illustrate the
capabilities of PML for contextualising these results.
Using the PML architecture to contextualise sentiment analysis data
The primary function of using the network of semantic links embedded within a PML
file is to enable data extracted from the textual content encoded within its
<content> elements, or referenced by the @sourceRef
attribute, to be contextualised. A number of ways in which this can be done will
illustrate something of its potential for enriching the output of linguistic
analyses.
Interrogating the corpus of PML data can be done by simple XPATH expressions
which follow the chain of linkages between data and metadata: although, for the
purpose of the tests documented here, these were used on the modified PML files
which included the texts of proceedings, they would work equally well using
externally held texts referenced by PML’s @sourceRef attribute. These
XPATH expressions may be used with XQUERY queries or within XSLT transformations
to produce the same results. For the purpose of this study, XSLT stylesheets
were written to generate the results shown although XQUERY can be just used as
effectively.
One obvious line of enquiry is to examine the sentiments expressed by individual
MPs. This is readily done by using the
@contributorID attribute shown
in Example 2 which links a contribution to the person making it. A simple XQUERY
or XSLT transformation can be used to extract the contributions made by a member
and perform a statistical analysis of the sentiments recorded within them. Here,
for instance, the positivity or negativity of comments on immigration by each
member for each of the years 2010-2014 are calculated and colour-coded by an
XSLT transformation to HTML:
In this chart the colour black indicates the most negative attitudes, reddish
brown those which tend to be more neutral and orange the most positive. Where no
comments on immigration were made by a member, N/A is shown.
Although this example shows only a very simple analysis, it does reveal some
interesting results. The then Home Secretary, Theresa May, tended initially to
express relatively neutral sentiments towards immigration but these grew
significantly more negative as the parliamentary term progressed. As Prime
Minister she has subsequently committed the country to leave the European single
market, the so-called “hard Brexit”, primarily to exert more
control on immigration. This simple analysis reveals that her negative views on
immigration formed over a number of years.
Although this is a relatively broad analysis which conflates all contributions by
a given member in a given year, more detailed ones may be carried out at any
level of granularity down to individual sessions or parts of sessions; this is
because PML incorporates a temporal element, <calendarObject>, to which
any contribution can be linked.
Another level of analysis may be carried out by the same simple statistical
technique and colour coding to visualise patterns of sentiment by political
party. This time use is made of an attribute,
@categoryID within
PML’s
<person> element: this includes an attribute which notes a member’s
place within a category such as party affiliation. Again a simple HTML table can
be generated by an XSLT transformation or an XQUERY query, although here the
breakdown of data is by month rather than year:
This analysis, which uses the same colour coding as Figure 1, shows the possibly
surprising result that there is little difference between the parties in their
(predominantly negative) sentiments expressed towards immigration during the
first year of this Parliament. The left-of-centre Labour party appears as
negative as the right-wing Conservative party. This may reflect the beginnings
of an initiative by the then Labour leader to attempt to make his party appear
tougher on immigration, which some at the time felt was an issue that had lost
them votes in the General Election of 2010, and which later led to more
pronounced comments and policies on this subject [
Miliband 2012].
A further level of analysis could extend this breakdown by party to incorporate
gender. This is readily done as the same categoryID mentioned above may be used
to delineate by gender. A simple modification of the XSLT stylesheet used to
generate Figure 2 produces the following breakdown by party and gender, again
using the same colour coding; this reveals little variation by this criterion
within each party:
More sophisticated analyses may be achieved by utilising a further feature of
PML, its extensive use of URIs to reference almost every component: these may
readily be used to interface with externally-held data. One interesting approach
to examining patterns of sentiment expressed in the proceedings is to consider
their geo-spatial dimension. Each constituency recorded in a PML file, for
instance, may be labelled with a URI which in turn can be used to generate
geo-data to enable visualisations demonstrating the geographical patterning of
the sentiments recorded in parliamentary speeches.
One approach to enabling this is to use files encoded in Keyhole Markup Language
(KML) [
Google Developers 2015] which have already been published to
cover UK parliamentary constituencies. These files, produced by MapIt UK [
MapIt UK 2015] cover all 650 UK constituencies and include detailed
boundary information for each of these. For the purpose of this demonstration,
the seventy-two files representing constituencies for Greater London were used.
To interface with the PML data, they had to be edited slightly to incorporate
the same URIs for constituencies as those found in the PML files.
Each KML file is run through an XSLT transformation or XQUERY query which
retrieves contributions by the member for each constituency, calculates the
relative weights of the positive, negative and neutral values in the sentiments
expressed within these, assigns a score from 1 to 100 based on these sentiments
and generates a colour code based on this value. This value then replaces the
one already present in the KML element that designates the fill colour for the
polygon defining the boundaries of each constituency. This process may be used
across the whole corpus or be restricted by date, down to a fine level of
granularity if required.
The resulting set of KML files may be used to generate colour-coded maps using
any compliant software. A sample output using Google Earth and covering Greater
London in the year 2010 is shown in Figure 4: the legend at the bottom of the
image indicates the range on the negative/positive spectrum within which the
MP's contributions fell during that year.
As may be expected in the most diverse and multi-cultural city in the United
Kingdom, most sentiments expressed towards immigration by London MPs tend
towards the positive, the only exception being those from the member for Mitcham
and Morden. Most London’s MPs did not comment on immigration during this period
and most of those who did come from the outer ring of constituencies, which are
generally more affluent and slightly more conservative than those of inner
London, but were nevertheless generally positive in their comments on this issue.
This is, of course, a visualisation of data from a single year, the year of the
General Election: it would be relatively simple to generate animated
visualisations representing any changing sentiments within this geographic area
over time.
Comparison with other approaches to parliamentary metadata
PML's rich set of semantic linkages for parliamentary metadata offers a
potentially more powerful base for machine-readable analysis than the other
approaches detailed above. At this point, it is useful to compare how its
approach differs from these.
Compared to the Portuguese metadata system discussed by [
Pinto et al. 2005], PML offers much finer granularity and more sophisticated linking. Pinto et
al's approach, designed to support an audiovisual delivery system of
parliamentary proceedings, only offers granularity down to the page level and a
simple XHTML encoding of the textual data [
Pinto et al. 2005, 2].
Its mapping of facets of the parliamentary record to DC is limited to a small
number (including legislature and session) and it includes none of the
contextual information, such as the information on members, gender and
geographical data, that PML can support. While functioning very efficiently in
its purpose to enable the audiovisual system it supports, it provides very
limited facilities for analysis of the type described here.
The Akomo Ntoso scheme provides a richer metadata set than the Portuguese for the
purpose of marking-up parliamentary documents, as it includes not only debates
but also acts, bills, reports and a number of other document types. Its element
set is, however, highly document-centred and its potential for encoding wider
contextual linkages more limited than PML’s. Much of its element set is derived
from XHTML and so most of its linking mechanisms use this schema's
@href attribute to point to externally-held ontologies. Much of
the contextualised analytic power of Akomo Ntoso will therefore depend on these
external sources and the semantic linkages that they enable: its internal
features remain limited for analyses of the type discussed here.
The Political Mashup (PM) schema is designed more specifically for analysis but
contains limited facilities within its architecture for encoding
machine-readable contextual information. The schema is designed specifically for
examining the structure of debates as events, and so adapts element sets from
the TEI designed for describing theatrical performance: it relies heavily, for
instance, on a semantically-imprecise element
<stage-direction> used to
describe most features of the proceedings except for speeches. As is the case
for Akomo Ntoso, the schema also uses simple identifiers to externally-held
metadata on which it relies for contextualisation: a speech, for instance, may
open as follows:
<speech pm:speaker="Andrew Miller" pm:party="Lab" pm:role="mp" pm:party-ref="uk.p.Lab" pm:member-ref="uk.m.10435"pm:id="uk.proc.d.2011-11-23.1.3.6">
Example 4.
sample Political Mashups element
None of the referents for these attributes are contained within the PM file: the
only metadata components within its architecture are simple Dublin Core elements
providing document-level descriptive metadata. Nor does the schema allow the
detailed voting analyses provided by PML as it encodes votes as procedural
markup, the application of which is inconsistently applied over time.
PML appears to offer a better alternative to these other XML approaches for
providing the contextual information by which the results of machine-generated
linguistic analyses may be enhanced. It offers more powerful and effective
mechanisms for contexualising the results of analyses within its
tightly-constrained but flexible structures.
Other potential uses of PML data
The above discussion is intended to illustrate the potential of using the PML
architecture and its semantic linkages in order to contextualise the results of
analyses based on the textual content of proceedings. The discussion
deliberately concentrates on using simple tools, notably XSLT transformations or
XQUERY queries, to extract and visualise the data.
Even with these simple tools interesting and revealing results can readily be
obtained. There is much scope for further analyses which could exploit the
potential of PML to provide new insights into the parliamentary record. Debates
currently taking place (at the time of writing) in the UK Parliament on
“Brexit”, the UK’s departure from the European Union, for
instance, may well yield interesting results when subjected to sentiment-based
analyses of this type. Similarly, in the current climate within the US, where
much debate appears to take place via Twitter, some potentially valuable
research could be undertaken on tracing sentiments within Congressional
proceedings and relating them to social media. Robust analyses of this type with
a quantitative evidence base could be most valuable and revealing in the current
political climate.
Some other avenues for research are possible within the PML architecture,
although at present these are limited because of the quality of textual corpora
available. A potentially powerful area would be to correlate a linguistic
analysis of a member's contributions to debates with their voting record. PML
allows for the detailed recording of voting patterns using an number of
attributes to <voteEvent>;, its container element for information on
votes or divisions. Using these a complete pattern of an individual's voting
record can be derived which could then be incorporated into such an analysis.
Unfortunately at present the voting data within most corpora is often a simple,
unstructured transcription of the proceedings text itself: to generate an
accurate set of data would require manual editing for which sufficient resources
have not yet been available. A complete and accurate set of voting data encoded
in PML would represent a valuable resource for historians and social
scientists.
The simple XSLT transformations used to visualise PML data could also be used as
the basis of interactive web-based services for presenting parliamentary data
for non-specialist users. They could, for instance, to used to provide
on-the-fly visualisations across the corpus, potentially enhancing web services
which are designed to enhance citizens’ access to legislative proceedings (such
as the service
They Work For You in the UK [
mySociety 2015]). Projects such as these could be facilitated
perhaps by producing modularised XSLT stylesheets for diverse sets of queries or
analyses. The sharing of such stylesheets throughout the academic and
extra-academic communities could significantly augment the usability of
PML-encoded data and make its potential for sophisticated access to the
parliamentary record more widely realised.
Conclusions
Being able to contextualise the results of fine-grained machine-generated
analyses of linguistic data offers the potential to enrich greatly their
findings. For the specific area of parliamentary proceedings, the approach
offered by Parliamentary Markup Language appears to offer great potential for
new avenues of research by allowing contextualisation of this type to be readily
achieved. When combined with resources external to the PML file itself, for
instance the MADS-encoded controlled vocabularies produced by the LIPARM
project, the scope for large-scale studies becomes readily achievable.
The range of potential analyses that could be performed with PML is wide-ranging:
they could include extensive diachronic historical analyses or on-the-fly
visualisations of current proceedings. PML corpora can provide an substantial
evidence base for sophisticated machine-readable analyses which extend well
beyond the resource discovery functions for which the schema was initially
devised. The use of electronic text corpora for parliamentary studies remains
relatively nascent, but its potential for seeding future research is clear.
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