NDLI: Determining Political Stances from Twitter Timelines: The Belgian Parliament Case

Content Provider	ACM Digital Library
Author	Boireau, Michaël
Abstract	Politicians' timelines on Twitter are here examined as an alternative source for text mining and analysis. The case of the Belgian Parliament is taken to illustrate how political stances expressed by MPs on Twitter help discriminate their position on a single dimension axis. In order to do so, their political position estimates are first calculated by means of Wordfish, an algorithm especially intended for retrieving ideological positioning of actors. The partisan influence on these estimates is then tested by ANOVA to check whether politicians are significantly different from one another along ideological lines. Results demonstrate that the classic Left-Right opposition is perceptible on Twitter as long as estimates calculated from the timelines show little variance among politicians belonging to the same party. A number of caveats are additionally given to produce best estimates based on Twitter timelines.
Starting Page	145
Ending Page	151
Page Count	7
File Format	PDF
ISBN	9781450334013
DOI	10.1145/2729104.2729114
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2014-11-18
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Text mining Salience theory Social media Twitter
Content Type	Text
Resource Type	Article

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Determining Political Stances from Twitter Timelines: The Belgian Parliament Case