Controversial Topic Discovery on Members of Congress with Twitter
Copyright policy )Controversial Topic Discovery on Members of Congress with Twitter
AbstractThis paper addresses how Twitter can be used for identifying conflict between communities of users. We aggregate documents by topic and by community and perform sentiment analysis, which allows us to analyze the overall opinion of each community about each topic. We rank the topics with opposing views (negative for one community and positive for the other). For illustration of the proposed methodology we chose a problem whose results can be evaluated using news articles. We look at tweets for republican and democrat congress members for the 112th House of Representatives from September to December 2013 and demonstrate that our approach is successful by comparing against articles in the news media.
- Missouri University of Science and Technology United States
- Syracuse University United States
Topic Modeling, Twitter, Polarizing Topics, Semantic Extraction, Latent Dirichlet Allocation, Social Media Mining
Topic Modeling, Twitter, Polarizing Topics, Semantic Extraction, Latent Dirichlet Allocation, Social Media Mining
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