A combination of opinion mining and social network techniques for discussion analysis
Résumé
Mining opinion data that reside in online discussions is a way to track
opinions of people on specific subjects. Many of the existing techniques model
a discussion as a social network of users and they represent it with a user-based
graph. In this paper we propose a new framework for discussion analysis. We
combine Social Network Analysis and Opinion Mining in order to give structure
to a discussion. Such techniques have not been combined until now.We propose
the use of an opinion-based graph whose vertices contain message objects and its
«reply-to» edges are labeled with opinion polarities. We compare the opinionbased
with the user-based graphs and we analyze the different information that
can be extracted from them. Our experiments validate the proposed framework
and show that the representation of discussions by opinion-based graphs gives
information that cannot be provided by a user-based graph.