Analyzing Discourse Communities with Distributional Semantic Models

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Title: Analyzing Discourse Communities with Distributional Semantic Models
Authors: Brigadir, Igor
Greene, Derek
Cunningham, Pádraig
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Date: 1-Jul-2015
Online since: 2015-06-17T11:32:49Z
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.
Funding Details: Science Foundation Ireland
Type of material: Conference Publication
Publisher: ACM
Copyright (published version): 2015 ACM
Keywords: Discourse-historical approachCritical discourse analysisPolitical discourseDistributional semanticsScottish independence referendumUS midterm electionsPolitics on twitter
DOI: 10.1145/2786451.2786470
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Language: en
Status of Item: Peer reviewed
Is part of: WebSci '15 Proceedings of the ACM Web Science Conference
Conference Details: ACM Web Science 2015 Conference, 28 June - 1 July 2015, Oxford, United Kingdom
Appears in Collections:Computer Science Research Collection
Insight Research Collection

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