Credibility Evaluation and Results with Leader-Weight in Opinion Mining

Abstract

A plethora of information is recently flooding the Internet with a rapid surge in Internet usage. Information easily available on the Internet help researchers understand people they study. The existing techniques of the opinion mining usually consist of sentiment classification, feature-based opinion mining, summarization, comparative sentence and relation mining, opinion search, opinion spam, and the linguistic dictionary construction such as the WordNet. This paper, however, proposes differing methods of opinion mining from existing ones. The methods we present here enable credibility evaluation and result conversion using influence of each opinion holder on the Internet and their personal information, which are an analysis-result of LIWC, including their background information and tendency.