A Survey of Outlier Detection Methodologies
Artificial Intelligence Review
The political blogosphere and the 2004 U.S. election: divided they blog
Proceedings of the 3rd international workshop on Link discovery
Get out the vote: determining support or opposition from congressional floor-debate transcripts
EMNLP '06 Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing
Sentiment in short strength detection informal text
Journal of the American Society for Information Science and Technology
The Effects of Query Bursts on Web Search
WI-IAT '10 Proceedings of the 2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 01
Democrats, republicans and starbucks afficionados: user classification in twitter
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
Patterns of influence in a recommendation network
PAKDD'06 Proceedings of the 10th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining
Analyzing the polarity of opinionated queries
ECIR'12 Proceedings of the 34th European conference on Advances in Information Retrieval
SIGIR '12 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
Mining web query logs to analyze political issues
Proceedings of the 3rd Annual ACM Web Science Conference
ECIR'13 Proceedings of the 35th European conference on Advances in Information Retrieval
Political hashtag hijacking in the U.S.
Proceedings of the 22nd international conference on World Wide Web companion
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What can user-generated online data tell us about political issues and partisan politics? How polarized is a web search query such as "climategate 2.0" and can we quantify the leaning of the hashtag #climatechange? We summarize recent work that studies U.S. politics using web search logs and Twitter data from the angle of political left-vs.-right polarization. With a simple yet effective methodology we discover a number of interesting findings. For example, we show a tendency for web search queries with a right leaning to surface more results with a negative sentiment, and we give a description of political hashtag hijacking where one political camp tries to \jam the frequency" of the other one. We end with a discussion of challenges and opportunities in the area of data-driven political science that might be of interest to researchers looking to apply knowledge management in an interdisciplinary setting.