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Extracting tip information from social media

Published: 03 December 2012 Publication History

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.

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IIWAS '12: Proceedings of the 14th International Conference on Information Integration and Web-based Applications & Services
December 2012
432 pages
ISBN:9781450313063
DOI:10.1145/2428736
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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  • @WAS: International Organization of Information Integration and Web-based Applications and Services

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 03 December 2012

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Author Tags

  1. experiment mining
  2. extracting information
  3. social network services

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IIWAS '12
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