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Analyzing Discourse Communities with Distributional Semantic Models

Publication Type: 
Refereed Conference Meeting Proceeding
This paper presents a new corpus-driven approach applica- ble to the study of language patterns in social and political contexts, or Critical Discourse Analysis (CDA) using Distri- butional Semantic Models (DSMs). This approach considers changes in word semantics, both over time and between com- munities with di ering viewpoints. The geometrical spaces constructed by DSMs or \word spaces" o er an objective, robust exploratory analysis tool for revealing novel patterns and similarities between communities, as well as highlight- ing when these changes occur. To quantify di erences be- tween word spaces built on di erent time periods and from di erent communities, we analyze the nearest neighboring words in the DSM, a process we relate to analyzing \concor- dance lines". This makes the approach intuitive and inter- pretable 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
Conference Name: 
ACM Web Science 2015 Conference
Digital Object Identifer (DOI): 
Publication Date: 
Conference Location: 
United Kingdom (excluding Northern Ireland)
National University of Ireland, Dublin (UCD)
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