The proliferation of blogs and social network sites means that the web now contains a huge amount of text written by individuals discussing the news and their everyday lives. This talk describes methods for downloading and processing blog and MySpace data on a large scale in order to identify topics attracting public interest as well as events falling within broad topics. In addition, the considerable practical issues involved with obtaining high quality data from the web will be discussed. The methods will be illustrated with case studies for Neda, Michael Jackson and public fears about scientific research. One application is the retrospective creation of automatic timelines of major events and another is to inform policy makers of news stories that attract particular public concern.
About
Mike Thelwall is Professor of Information Science and leader of the Statistical Cybermetrics Research Group at the University of Wolverhampton, UK. He is also visiting fellow of the Amsterdam Virtual Knowledge Studio, a Docent at Abo Akademi University Department of Information Studies, and a research associate at the Oxford Internet Institute. He has developed tools for downloading and analysing web sites, blogs and social networking sites, including the research web crawler SocSciBot and software for statistical and topological analyses of site structures (through links) and site content (through text). He has published 150 refereed journal articles, seven book chapters, two books including Introduction to Webometrics, is an associate editor of the Journal of the American Society for Information Science and Technology and sits on eight other editorial boards.
Read more at http://www.scit.wlv.ac.uk/~cm1993/mycv.html
This talk will discuss how commercial customers can benefit from natural language processing.
About
Mark Rogers is CEO of Market Sentinel.