articleOct 1, 2011Closed access
Predicting the Political Alignment of Twitter Users
Indiana University Bloomington
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Abstract
The widespread adoption of social media for political communication creates unprecedented opportunities to monitor the opinions of large numbers of politically active individuals in real time. However, without a way to distinguish between users of opposing political alignments, conflicting signals at the individual level may, in the aggregate, obscure partisan differences in opinion that are important to political strategy. In this article we describe several methods for predicting the political alignment of Twitter users based on the content and structure of their political communication in the run-up to the 2010 U.S. midterm elections. Using a data set of 1,000 manually-annotated individuals, we find that a…
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Topics
Keywords
- Computer science
- Support vector machine
- Politics
- Metadata
- Topic model
- Social media
- Classifier (UML)
- Public opinion
UN Sustainable Development Goals
- Peace, Justice and strong institutions
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