Proceedings of the thirteenth ACM international conference on Information and knowledge management
The political blogosphere and the 2004 U.S. election: divided they blog
Proceedings of the 3rd international workshop on Link discovery
Building bridges for web query classification
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Exploring the characteristics of opinion expressions for political opinion classification
dg.o '08 Proceedings of the 2008 international conference on Digital government research
Opinion Mining and Sentiment Analysis
Foundations and Trends in Information Retrieval
The Myth of Digital Democracy
Meme-tracking and the dynamics of the news cycle
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
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
Learning document aboutness from implicit user feedback and document structure
Proceedings of the 18th ACM conference on Information and knowledge management
Highlighting disputed claims on the web
Proceedings of the 19th international conference on World wide web
The demographics of web search
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
Statement map: reducing web information credibility noise through opinion classification
AND '10 Proceedings of the fourth workshop on Analytics for noisy unstructured text data
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
Who uses web search for what: and how
Proceedings of the fourth ACM international conference on Web search and data mining
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics: Posters
Proceedings of the ACM 2011 conference on Computer supported cooperative work
Information credibility on twitter
Proceedings of the 20th international conference on World wide web
Computing political preference among twitter followers
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Democrats, republicans and starbucks afficionados: user classification in twitter
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
Mining contrastive opinions on political texts using cross-perspective topic model
Proceedings of the fifth ACM international conference on Web search and data mining
Opinions network for politically controversial topics
Proceedings of the first edition workshop on Politics, elections and data
Proceedings of the sixth ACM international conference on Web search and data mining
ECIR'13 Proceedings of the 35th European conference on Advances in Information Retrieval
Inferring the demographics of search users: social data meets search queries
Proceedings of the 22nd international conference on World Wide Web
Secular vs. Islamist polarization in Egypt on Twitter
Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
PLEAD 2013: politics, elections and data
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
Analyzing, Detecting, and Exploiting Sentiment in Web Queries
ACM Transactions on the Web (TWEB)
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We present a novel approach to using anonymized web search query logs to analyze and visualize political issues. Our starting point is a list of politically annotated blogs (left vs. right). We use this list to assign a numerical political leaning to queries leading to clicks on these blogs. Furthermore, we map queries to Wikipedia articles and to fact-checked statements from politifact.com, as well as applying sentiment analysis to search results. With this rich, multi-faceted data set we obtain novel graphical visualizations of issues and discover connections between the different variables. Our findings include (i) an interest in "the other side" where queries about Democrat politicians have a right leaning and vice versa, (ii) evidence that "lies are catchy" and that queries pertaining to false statements are more likely to attract large volumes, and (iii) the observation that the more right-leaning a query it is, the more negative sentiments can be found in its search results.