research-article

Analyzing Discourse Communities with Distributional Semantic Models

Authors:

Pádraig CunninghamAuthors Info & Claims

WebSci '15: Proceedings of the ACM Web Science Conference

Article No.: 27, Pages 1 - 10

https://doi.org/10.1145/2786451.2786470

Published: 28 June 2015 Publication History

Abstract

This paper presents a new corpus-driven approach applicable to the study of language patterns in social and political contexts, or Critical Discourse Analysis (CDA) using Distributional Semantic Models (DSMs). This approach considers changes in word semantics, both over time and between communities with differing viewpoints. The geometrical spaces constructed by DSMs or "word spaces" offer an objective, robust exploratory analysis tool for revealing novel patterns and similarities between communities, as well as highlighting when these changes occur. To quantify differences between word spaces built on different time periods and from different communities, we analyze the nearest neighboring words in the DSM, a process we relate to analyzing "concordance lines". This makes the approach intuitive and interpretable to practitioners. We demonstrate the usefulness of the approach with two case studies, following groups with opposing political ideologies in the Scottish Independence Referendum, and the US Midterm Elections 2014.

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Cited By

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cover image ACM Conferences

WebSci '15: Proceedings of the ACM Web Science Conference

June 2015

366 pages

ISBN:9781450336727

DOI:10.1145/2786451

Conference Chair:
David De Roure,
Program Chairs:
Pete Burnap,
Susan Halford

Copyright © 2015 ACM.

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Published: 28 June 2015

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WebSci '15: ACM Web Science Conference

June 28 - July 1, 2015

Oxford, United Kingdom

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Overall Acceptance Rate 245 of 933 submissions, 26%

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Cited By

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https://doi.org/10.17533/udea.iee.v42n2e12
Garcia JFernández Pedemonte DVaca CBaquerizo-Neira M(2024)A Pertinence Score for Political Discourse Analysis: The Case of 2018 Colombian ElectionsDigital Government: Research and Practice10.1145/36892135:3(1-15)Online publication date: 8-Oct-2024
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Yantseva V(2024)Climate change denial and ideology in Swedish online media: measuring ideology change using a computational approachJournal of Computational Social Science10.1007/s42001-024-00343-x8:1Online publication date: 16-Dec-2024
https://doi.org/10.1007/s42001-024-00343-x
Yantseva V(2022)Discursive construction of migrant otherness on Facebook: A distributional semantics approachDiscourse & Society10.1177/0957926522111701434:2(236-254)Online publication date: 21-Oct-2022
https://doi.org/10.1177/09579265221117014
Németh R(2022)A scoping review on the use of natural language processing in research on political polarization: trends and research prospectsJournal of Computational Social Science10.1007/s42001-022-00196-26:1(289-313)Online publication date: 19-Dec-2022
https://doi.org/10.1007/s42001-022-00196-2
Liu JSinghal TBlessing LWood KLim K(2020)EPIC30M: An Epidemics Corpus of Over 30 Million Relevant Tweets2020 IEEE International Conference on Big Data (Big Data)10.1109/BigData50022.2020.9377739(1206-1215)Online publication date: 10-Dec-2020
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Wu ZLi CZhao ZWu FMei QCollins-Thompson KMei QDavison BLiu YYilmaz E(2018)Identify Shifts of Word Semantics through Bayesian SurpriseThe 41st International ACM SIGIR Conference on Research & Development in Information Retrieval10.1145/3209978.3210040(825-834)Online publication date: 27-Jun-2018
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Fraisier OCabanac GPitarch YBesançon RBoughanem MLee DSastry NWeber I(2018)Stance Classification through Proximity-based Community DetectionProceedings of the 29th on Hypertext and Social Media10.1145/3209542.3209549(220-228)Online publication date: 3-Jul-2018
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Quraishi MFafalios PHerder EAkkermans HFontaine KVermeulen IHouben GWeber M(2018)Viewpoint Discovery and Understanding in Social NetworksProceedings of the 10th ACM Conference on Web Science10.1145/3201064.3201076(47-56)Online publication date: 15-May-2018
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Thonet TCabanac GBoughanem MPinel-Sauvagnat KLim EWinslett MSanderson MFu ASun JCulpepper SLo EHo JDonato DAgrawal RZheng YCastillo CSun ATseng VLi C(2017)Users Are Known by the Company They KeepProceedings of the 2017 ACM on Conference on Information and Knowledge Management10.1145/3132847.3132897(87-96)Online publication date: 6-Nov-2017
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