Machine Learning
Introduction to Modern Information Retrieval
Introduction to Modern Information Retrieval
Statistical models of topical content
Topic detection and tracking
The political blogosphere and the 2004 U.S. election: divided they blog
Proceedings of the 3rd international workshop on Link discovery
Exploiting subjectivity analysis in blogs to improve political leaning categorization
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Opinion Mining and Sentiment Analysis
Foundations and Trends in Information Retrieval
Blogs are Echo Chambers: Blogs are Echo Chambers
HICSS '09 Proceedings of the 42nd Hawaii International Conference on System Sciences
NewsCube: delivering multiple aspects of news to mitigate media bias
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Aspect-level news browsing: understanding news events from multiple viewpoints
Proceedings of the 15th international conference on Intelligent user interfaces
News comments: exploring, modeling, and online prediction
ECIR'2010 Proceedings of the 32nd European conference on Advances in Information Retrieval
Identifying ideological perspectives in text and video
Identifying ideological perspectives in text and video
Care to comment?: recommendations for commenting on news stories
Proceedings of the 21st international conference on World Wide Web
Mining web query logs to analyze political issues
Proceedings of the 3rd Annual ACM Web Science Conference
Discovering habits of effective online support group chatrooms
Proceedings of the 17th ACM international conference on Supporting group work
Diversifying user comments on news articles
WISE'12 Proceedings of the 13th international conference on Web Information Systems Engineering
Characterizing and curating conversation threads: expansion, focus, volume, re-entry
Proceedings of the sixth ACM international conference on Web search and data mining
Ontology-based sentiment analysis of twitter posts
Expert Systems with Applications: An International Journal
Challenges and opportunities of local journalism: a case study of the 2012 Korean general election
Proceedings of the 5th Annual ACM Web Science Conference
Echo: the editor's wisdom with the elegance of a magazine
Proceedings of the 5th ACM SIGCHI symposium on Engineering interactive computing systems
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Political views frequently conflict in the coverage of contentious political issues, potentially causing serious social problems. We present a novel social annotation analysis approach for identification of news articles' political orientation. The approach focuses on the behavior of individual commenters. It uncovers commenters' sentiment patterns towards political news articles, and predicts the political orientation from the sentiments expressed in the comments. It takes advantage of commenters' participation as well as their knowledge and intelligence condensed in the sentiment of comments, thereby greatly reduces the high complexity of political view identification. We conduct extensive study on commenters' behaviors, and discover predictive commenters showing a high degree of regularity in their sentiment patterns. We develop and evaluate sentiment pattern-based methods for political view identification.