Extracting tip information from social media

  • Authors:

  • Yuki Hattori;Akiyo Nadamoto

  • Affiliations:

  • Konan University, Higashinada-ku Kobe, Japan;Konan University, Higashinada-ku Kobe, Japan

  • Venue:
  • Proceedings of the 14th International Conference on Information Integration and Web-based Applications & Services
  • Year:
  • 2012

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Abstract

Using social media, users post and exchange information related to personal behavior, experimentation, and personal sentiment. Sometimes this information is not written in ordinary web pages. This information is important for users who are people of the community and for people outside of the community. Nevertheless, it is difficult to extract important information from social media because such services include so much information. Moreover, the information quality differs. We designate such important and unique information related to social media as "tip information". As described in this paper, we propose a method to extract credible and important tip information from SNSs as a first step in extracting tip information from social media. Then we propose a means to extract tip information from SNS, and propose a means of ranking the tip information.