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Web Science 2.0: Identifying Trends Through Semantic Social Network Analysis

Peter Gloor
Massachusetts Institute of Technology (MIT)

Jonas S. Krauss
University of Northwestern Switzerland

Stefan Nann
University of Northwestern Switzerland

Kai Fischbach
University of Cologne; MIT Center for Collective Intelligence

Detlef Schoder
University of Cologne

November 11, 2008


Abstract:     
We introduce a novel set of social network analysis based algorithms for mining the Web, blogs, and online forums to identify trends and find the people launching these new trends. These algorithms have been implemented in Condor, a software system for predictive search and analysis of the Web and especially social networks.We illustrate our approach by qualitatively comparing Web buzz and our Web betweenness for the 2008 US presidential elections, as well as correlating the Web buzz index with share prices.

Keywords: trend prediction,social network analysis,semantic analysis

JEL Classifications: O31

Working Paper Series

Date posted: November 16, 2008 ; Last revised: January 06, 2009

Suggested Citation

Gloor, Peter, Krauss, Jonas S., Nann, Stefan, Fischbach, Kai and Schoder, Detlef, Web Science 2.0: Identifying Trends Through Semantic Social Network Analysis (November 11, 2008). Available at SSRN: http://ssrn.com/abstract=1299869


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Contact Information

Peter Gloor (Contact Author)
Massachusetts Institute of Technology (MIT) ( email )
77 Massachusetts Avenue
50 Memorial Drive
Cambridge, MA 02139-4307
United States
Kai Fischbach
University of Cologne ( email )
Pohligstr. 1
Cologne D-50969
Germany
MIT Center for Collective Intelligence ( email )
Cambridge, MA 02142
United States
Jonas S. Krauss
University of Northwestern Switzerland ( email )
Brugg Switzerland
Stefan Nann
University of Northwestern Switzerland ( email )
Brugg Switzerland
Detlef Schoder
University of Cologne ( email )
Pohligstr. 1
Cologne D-50969
Germany
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