The Politics of Comments: Predicting Political Orientation of News Stories with Commentators' Sentiment Patterns

Speaker:	Souneil Park
		KAIST, Korea

Title:		"The Politics of Comments: Predicting Political
		 Orientation of News Stories with Commentators'
		 Sentiment Patterns"

Date:		Friday, 25 March 2011

Time:		10:30am  - 11:30am

Venue:		Room 2612A (via lifts 31/32), HKUST

Abstract:

Political views frequently conflict in the coverage of contentious
political issues, potentially causing serious social problems. While much
useful to users, it is very difficult to analyse news articles and
identify the political views of news articles. We develop an important
method which identifies political orientation of news stories without
complex news text analysis. Admitting the practical limitation of news
text analysis, the method takes advantage of commentators' participation
as well as their knowledge and intelligence; their interpretation of the
political orientation is condensed in the sentiment of comments. Based on
extensive study on commentators' behaviors, it further notes and verifies
that there exist predictive commentators with a clear political preference
and that they are highly likely to show their views consistently towards
various political issues. They actively express their preferences
responding to the political news articles, showing a high degree of
regularity in their sentiment patterns. The sentiment expressed in their
comments is a strong indicator of the political orientation of an article.
Also, comments are usually concise, often express sentiments explicitly,
and easier to analyze. The use of these predictive commentators and their
comments greatly reduces the high complexity of political view
identification.

This work is published in ACM CSCW 2011.

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Biography:

Souneil Park is a Ph.D candidate in KAIST, Daejeon, Korea. He currently
conducts interdisciplinary research combining mass communication with
computer science. His research interest includes Internet journalism,
social media applications, web science, and human computer interaction.