カワベ タカシ   KAWABE Takashi
  川邉 孝
   所属   東京電機大学  システムデザイン工学部 人間科学系列(システムデザイン工学部)
   東京電機大学  情報環境学部 ※2017年度学生募集停止 情報環境学科 ※2017年度学生募集停止
   職種   教授
言語種別 英語
発行・発表の年月 2015/05
形態種別 学術研究論文
査読 査読有り
標題 "Tweet Credibility Analysis Evaluation by Improving Sentiment Dictionary"
執筆形態 共著
掲載誌名 Proc. of 2015 IEEE Congress on Evolutionary Computation (CEC2015)
掲載区分国外
出版社・発行元 CEC
巻・号・頁 pp.2354-2361
概要 The accuracy of the originally proposed method was susceptible since the sentiment opinion of most tweets was identified negative by the baseline
(namely Takamura's) semantic orientation dictionary. To cope with this problem, a method for extracting sentiment orientations of words and phrases is also proposed to improve the evaluation for analyzing the credibility of tweet
information. This method 1) evolutionally learns from a large amount of social data on Twitter, 2) focuses on adjective predicates, and 3) considers co-occurrences with negation expressions or multiple adjectives, between subjects and predicates, etc. The effects are proven by experiments using a large number of real tweets, in which we could detect rumor tweet much more accurately.