Detecting informative messages based on user history in twitter

Chang Woo Chun, Jung Tae Lee, Seung Wook Lee, Hae-Chang Rim

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Since more and more users participate in various social networking services, the volume of streaming data is considerably increasing. It is necessary to find out valuable messages from huge data archived every moment. This paper investigates the problem of detecting informative messages in Twitter, and proposes effective methods to solve the problem based on User History. Most of the sheer information in tweets has a common defect which is the fact that it is affected by influence of User level within the Twitter network. Our key idea is to leverage each user's history observed from a large scale dataset as features to determine whether a new message is informative or not, compared to their previous messages. This allows us to normalize influence of individual user on tweets and to estimate the probability of informativeness. Experimental results on a real Twitter data show that our method can effectively improve the performance on identifying informative tweets.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages162-173
Number of pages12
Volume7675 LNCS
DOIs
Publication statusPublished - 2012 Dec 31
Event8th Asia Information Retrieval Societies Conference, AIRS 2012 - Tianjin, China
Duration: 2012 Dec 172012 Dec 19

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7675 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other8th Asia Information Retrieval Societies Conference, AIRS 2012
CountryChina
CityTianjin
Period12/12/1712/12/19

Fingerprint

Defects
Streaming Data
Normalize
Social Networking
Leverage
History
Moment
Necessary
Experimental Results
Estimate
Influence

Keywords

  • Information filtering
  • Recommendation system
  • Social media
  • Twitter

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Chun, C. W., Lee, J. T., Lee, S. W., & Rim, H-C. (2012). Detecting informative messages based on user history in twitter. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7675 LNCS, pp. 162-173). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7675 LNCS). https://doi.org/10.1007/978-3-642-35341-3_14

Detecting informative messages based on user history in twitter. / Chun, Chang Woo; Lee, Jung Tae; Lee, Seung Wook; Rim, Hae-Chang.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 7675 LNCS 2012. p. 162-173 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7675 LNCS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Chun, CW, Lee, JT, Lee, SW & Rim, H-C 2012, Detecting informative messages based on user history in twitter. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). vol. 7675 LNCS, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 7675 LNCS, pp. 162-173, 8th Asia Information Retrieval Societies Conference, AIRS 2012, Tianjin, China, 12/12/17. https://doi.org/10.1007/978-3-642-35341-3_14
Chun CW, Lee JT, Lee SW, Rim H-C. Detecting informative messages based on user history in twitter. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 7675 LNCS. 2012. p. 162-173. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-642-35341-3_14
Chun, Chang Woo ; Lee, Jung Tae ; Lee, Seung Wook ; Rim, Hae-Chang. / Detecting informative messages based on user history in twitter. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 7675 LNCS 2012. pp. 162-173 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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