Quantising Opinions for Political Tweets Analysis
作者： Yulan He , Zhongyu Wei , Hassan Saif , Kam-Fai Wong
DOI:
关键词:
摘要: There have been increasing interests in recent years analyzing tweet messages relevant to political events so as understand public opinions towards certain issues. We analyzed crawled during the eight weeks leading UK General Election May 2010 and found that activities at Twitter is not necessarily a good predictor of popularity parties. then proceed propose statistical model for sentiment detection with side information such emoticons hash tags implying polarities being incorporated. Our results show analysis based on simple keyword matching against lexicon or supervised classifier trained distant supervision does correlate well actual election results. However, using our proposed analysis, we were able map opinion offline real world.
aclweb.org参考文章(13)
Patrick Paroubek, Alexander Pak, Twitter as a Corpus for Sentiment Analysis and Opinion Mining language resources and evaluation. ,(2010)
Jacob Ratkiewicz, Alessandro Flammini, Michael D. Conover, Filippo Menczer, Bruno Gonçalves, Matthew R. Francisco, Political Polarization on Twitter international conference on weblogs and social media. ,(2011)
Matthew P. Simmons, Avishay Livne, Eytan Adar, Lada A. Adamic, The Party Is Over Here: Structure and Content in the 2010 Election international conference on weblogs and social media. ,(2011)
Alberto Pepe, Johan Bollen, Huina Mao, Modeling Public Mood and Emotion: Twitter Sentiment and Socio-Economic Phenomena international conference on weblogs and social media. ,(2011)
Andranik Tumasjan, Isabell M. Welpe, Philipp G. Sandner, Timm Oliver Sprenger, Predicting Elections with Twitter: What 140 Characters Reveal about Political Sentiment international conference on weblogs and social media. ,(2010)
Rebecca Passonneau, Ilia Vovsha, Owen Rambow, Boyi Xie, Apoorv Agarwal, Sentiment Analysis of Twitter Data Proceedings of the Workshop on Language in Social Media (LSM 2011). pp. 30- 38 ,(2011)
David A. Shamma, Nicholas A. Diakopoulos, Characterizing debate performance via aggregated twitter sentiment human factors in computing systems. pp. 1195- 1198 ,(2010) , 10.1145/1753326.1753504
Tiong‐Thye Goh, Yen‐Pei Huang, Monitoring youth depression risk in Web 2.0 Vine. ,vol. 39, pp. 192- 202 ,(2009) , 10.1108/03055720911003969
Chenghua Lin, Yulan He, Joint sentiment/topic model for sentiment analysis conference on information and knowledge management. pp. 375- 384 ,(2009) , 10.1145/1645953.1646003
Bryan R. Routledge, Ramnath Balasubramanyan, Noah A. Smith, Brendan O'Connor, From Tweets to Polls: Linking Text Sentiment to Public Opinion Time Series international conference on weblogs and social media. ,(2010)