Web Science 2.0: Identifying Trends through Semantic Social Network Analysis
Name
Gloor-2009-Web science 2.0 identifying trends through semantic social network analysis.pdf
Size
1.81 MB
Format
Adobe PDF
Checksum (MD5)
6c90019aae34a8180f411d56da14a1a9
Author(s)
Gloor, Peter A.
Krauss, Jonas
Nann, Stefan
Fischbach, Kai
Schoder, Detlef
Date Issued
October 2009
Journal
International Conference on Computational Science and Engineering, 2009. CSE '09
Publisher
Institute of Electrical and Electronics Engineers
Citation
Gloor, P.A. et al. “Web Science 2.0: Identifying Trends through Semantic Social Network Analysis.” Computational Science and Engineering, 2009. CSE '09. International Conference on. 2009. 215-222. ©2009 Institute of Electrical and Electronics Engineers.
Version
Final published version
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. Algorithms include the temporal computation of network centrality measures, the visualization of social networks as Cybermaps, a semantic process of mining and analyzing large amounts of text based on social network analysis, and sentiment analysis and information filtering methods. The temporal calculation of betweenness of concepts permits to extract and predict long-term trends on the popularity of relevant concepts such as brands, movies, and politicians. 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.
Subjects
Web mining
Social network analysis
semantic social network analysis
trend prediction
MIT Department
Massachusetts Institute of Technology. Center for Collective Intelligence
Terms of Use
Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1109/CSE.2009.186
