Context Comparison of Bursty Events in Web Search and Online Media

In this paper, we conducted a systematic comparative analysis of language in different contexts of bursty topics, including web search, news media, blogging, and social bookmarking. We analyze (1) the content similarity and predictability between contexts, (2) the coverage of search content by each context, and (3) the intrinsic coherence of information in each context. Our experiments show that social bookmarking is a better predictor to the bursty search queries, but news media and social blogging media have a much more compelling coverage. This comparison provides insights on how the search behaviors and social information sharing behaviors of users are correlated to the professional news media in the context of bursty events.

[1]  Kenneth Ward Church,et al.  Query suggestion using hitting time , 2008, CIKM '08.

[2]  Lawrence Birnbaum,et al.  TagAssist: Automatic Tag Suggestion for Blog Posts , 2007, ICWSM.

[3]  Filip Radlinski,et al.  Query chains: learning to rank from implicit feedback , 2005, KDD '05.

[4]  Andreas Hotho,et al.  A Comparison of Social Bookmarking with Traditional Search , 2008, ECIR.

[5]  D. A. Field.  Laplacian smoothing and Delaunay triangulations , 1988 .

[6]  Slava M. Katz,et al.  Estimation of probabilities from sparse data for the language model component of a speech recognizer , 1987, IEEE Trans. Acoust. Speech Signal Process..

[7]  Steven Skiena,et al.  Newspapers vs. Blogs: Who Gets the Scoop? , 2006, AAAI Spring Symposium: Computational Approaches to Analyzing Weblogs.

[8]  Ted Pedersen,et al.  WordNet::Similarity - Measuring the Relatedness of Concepts , 2004, NAACL.

[9]  Ee-Peng Lim,et al.  Searching blogs and news: a study on popular queries , 2008, SIGIR '08.

[10]  Yong Yu,et al.  Optimizing web search using social annotations , 2007, WWW '07.

[11]  Michael Gamon,et al.  BLEWS: Using Blogs to Provide Context for News Articles , 2008, ICWSM.

[12]  Dimitrios Gunopulos,et al.  Identifying similarities, periodicities and bursts for online search queries , 2004, SIGMOD '04.

[13]  Jon M. Kleinberg,et al.  Bursty and Hierarchical Structure in Streams , 2002, Data Mining and Knowledge Discovery.

[14]  Georgia Koutrika,et al.  Can social bookmarking improve web search? , 2008, WSDM '08.

[15]  Susan T. Dumais,et al.  Newsjunkie: providing personalized newsfeeds via analysis of information novelty , 2004, WWW '04.

[16]  Ravi Kumar,et al.  On the Bursty Evolution of Blogspace , 2003, WWW '03.

[17]  Camille Roth,et al.  Intertemporal Topic Correlations in Online Media: A Comparative Study on Weblogs and News Websites , 2007, ICWSM.

[18]  Wolfgang Nejdl,et al.  Can all tags be used for search? , 2008, CIKM '08.

[19]  Benjamin Rey,et al.  Generating query substitutions , 2006, WWW '06.

[20]  Robert L. Grossman,et al.  Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining , 2005, KDD 2005.

[21]  Andrei Broder,et al.  A taxonomy of web search , 2002, SIGF.

[22]  Fernando Diaz,et al.  Integration of news content into web results , 2009, WSDM '09.

[23]  Brian N. Bershad,et al.  Why we search: visualizing and predicting user behavior , 2007, WWW '07.

[24]  Ramanathan V. Guha,et al.  The predictive power of online chatter , 2005, KDD '05.