Referral Web: combining social networks and collaborative filtering
Communications of the ACM
Measuring errors in text entry tasks: an application of the Levenshtein string distance statistic
CHI '01 Extended Abstracts on Human Factors in Computing Systems
You Are Who You Talk To: Detecting Roles in Usenet Newsgroups
HICSS '06 Proceedings of the 39th Annual Hawaii International Conference on System Sciences - Volume 03
Friends, foes, and fringe: norms and structure in political discussion networks
dg.o '06 Proceedings of the 2006 international conference on Digital government research
POLYPHONET: An advanced social network extraction system from the Web
Web Semantics: Science, Services and Agents on the World Wide Web
Extracting Social Networks Among Various Entities on the Web
ESWC '07 Proceedings of the 4th European conference on The Semantic Web: Research and Applications
Flink: Semantic Web technology for the extraction and analysis of social networks
Web Semantics: Science, Services and Agents on the World Wide Web
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Forums on the Internet are an overwhelming source of knowledge considering the number of topics treated and users who participate in these discussions. This volume of data is difficult to comprehend for a person with respect for the large number of posts. Our work proposes a new formal framework for synthesizing information contained in these forums. We extract a social network that reflects reality by extracting multiple relationships between individuals (structural relationship, name and text quotation relationships). These relationships are created from the structure and the content of the discussion. Results show that discovering quotation relationships from forums is not trivial.