From Big Data to Argument Analysis and Automated Extraction: A Selective Study of Argument in the Philosophy of Animal Psychology from the Volumes of the Hathi Trust Collection

Project report


McAlister, Simon, Allen, Colin, Ravenscroft, A., Reed, Chris, Bourget, David, Lawrence, John, Börner, Katy and Light, Robert 2014. From Big Data to Argument Analysis and Automated Extraction: A Selective Study of Argument in the Philosophy of Animal Psychology from the Volumes of the Hathi Trust Collection. Digging by Debating.
AuthorsMcAlister, Simon, Allen, Colin, Ravenscroft, A., Reed, Chris, Bourget, David, Lawrence, John, Börner, Katy and Light, Robert
TypeProject report
Abstract

The Digging by Debating (DbyD) project aimed to identify, extract, model, map and visualise
philosophical arguments in very large text repositories such as the Hathi Trust. The project
has: 1) developed a method for visualizing points of contact between philosophy and the
sciences; 2) used topic modeling to identify the volumes, and pages within those volumes,
which are ‘rich’ in a chosen topic; 3) used a semiformal
discourse analysis technique to
manually identify key arguments in the selected pages; 4) used the OVA argument mapping
tool to represent and map the key identified arguments and provide a framework for
comparative analysis; 5) devised and used a novel analysis framework applied to the
mapped arguments covering role, content and source of propositions, and the importance,
context and meaning of arguments; 6) created a prototype tool for identifying propositions,
using naive Bayes classifiers, and for identifying argument structure in chosen texts, using
propositional similarity; 7) created tools to apply topic modeling to tasks of rating similarity of
papers in the PhilPapers repository. The methods from 1 to 5 above, have enabled us to
locate and extract the key arguments from each text. It is significant that, in applying the
methods, a nonexpert
with limited or no domain knowledge of philosophy has both identified
the volumes of interest from a key ‘Big Data Set’ (Hathi Trust) AND identified key arguments
within these texts. This provided several key insights about the nature and form of arguments
in historical texts, and is a proofofconcept
design for a tool that will be usable by scholars.
We have further created a dataset with which to train and test prototype tools for both
proposition and argument extraction. Though at an early stage, these preliminary results are
promising given the complexity of the task.
Specifically, we have prototyped a set of tools and methods that allow scholars to move
between macroscale,
global views of the distributions of philosophical themes in such
repositories, and microscale
analyses of the arguments appearing on specific pages in texts
belonging to the repository. Our approach spans bibliographic analysis, science mapping,
and LDA topic modeling conducted at Indiana University and machineassisted
argument
markup into Argument Interchange Format (AIF) using the OVA (Online Visualization of
Argument) tool from the University of Dundee, where the latter has been used to analyse and
represent arguments by the team based at the University of East London, who also
performed a detailed empirical analysis of arguments in selected texts. This work has been
articulated as a proof of concept tool – linked to the repository PhilPapers – designed by
members linked to the University of London. This project is showing for the first time how big
data text processing techniques can be combined with deep structural analysis to provide
researchers and students with navigation and interaction tools for engaging with the large and
rich resources provided by datasets such as the Hathi Trust and PhilPapers. Ultimately our
efforts show how the computational humanities can bridge the gulf between the “big data”
perspective of firstgeneration
digital humanities and the close readings of text that are the
“bread and butter” of more traditional scholarship in the humanities.

Year2014
PublisherDigging by Debating
Web address (URL)http://diggingbydebating.org/wp-content/uploads/2014/04/DiggingbyDebating-FinalReport2.pdf
Publication dates
PrintApr 2014
Publication process dates
Deposited11 Oct 2017
Copyright information© 2014 The authors
Publisher's version
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