Web Science 2.0: Identifying Trends Through Semantic Social Network Analysis

32 Pages Posted: 16 Nov 2008

See all articles by Peter A. Gloor

Peter A. 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

Date Written: 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 Classification: O31

Suggested Citation

Gloor, Peter A. and Krauss, Jonas S. and Nann, Stefan and Fischbach, Kai and Schoder, Detlef, Web Science 2.0: Identifying Trends Through Semantic Social Network Analysis (November 11, 2008). Available at SSRN: https://ssrn.com/abstract=1299869 or http://dx.doi.org/10.2139/ssrn.1299869

Peter A. Gloor (Contact Author)

Massachusetts Institute of Technology (MIT) ( email )

77 Massachusetts Avenue
50 Memorial Drive
Cambridge, MA 02139-4307
United States

Jonas S. Krauss

University of Northwestern Switzerland ( email )

Brugg
Switzerland

Stefan Nann

University of Northwestern Switzerland ( email )

Brugg
Switzerland

Kai Fischbach

University of Cologne ( email )

Pohligstr. 1
Cologne, D-50969
Germany

MIT Center for Collective Intelligence ( email )

100 Main Street
E62-416
Cambridge, MA 02142
United States

Detlef Schoder

University of Cologne ( email )

Pohligstr. 1
Cologne, D-50969
Germany

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