Joint topic modeling for event summarization across news and social media streams

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

47 Citations (Scopus)

Abstract

Social media streams such as Twitter are regarded as faster first-hand sources of information generated by massive users. The content diffused through this channel, although noisy, provides important complement and sometimes even a substitute to the traditional news media reporting. In this paper, we propose a novel unsupervised approach based on topic modeling to summarize trending subjects by jointly discovering the representative and complementary information from news and tweets. Our method captures the content that enriches the subject matter by reinforcing the identification of complementary sentence-tweet pairs. To valuate the complementarity of a pair, we leverage topic modeling formalism by combining a two-dimensional topic-aspect model and a cross-collection approach in the multi-document summarization literature. The final summaries are generated by co-ranking the news sentences and tweets in both sides simultaneously. Experiments give promising results as compared to state-of-the-art baselines.

Original languageEnglish
Title of host publicationACM International Conference Proceeding Series
Pages1173-1182
Number of pages10
DOIs
Publication statusPublished - 19 Dec 2012
Event21st ACM International Conference on Information and Knowledge Management, CIKM 2012 - Maui, HI, United States
Duration: 29 Oct 20122 Nov 2012

Other

Other21st ACM International Conference on Information and Knowledge Management, CIKM 2012
CountryUnited States
CityMaui, HI
Period29/10/122/11/12

Fingerprint

Experiments

Keywords

  • complementary summary
  • cross-collection topic-aspect model
  • gibbs sampling
  • lda

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition
  • Software

Cite this

Joint topic modeling for event summarization across news and social media streams. / Gao, Wei; Li, Peng; Darwish, Kareem.

ACM International Conference Proceeding Series. 2012. p. 1173-1182.

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

Gao, W, Li, P & Darwish, K 2012, Joint topic modeling for event summarization across news and social media streams. in ACM International Conference Proceeding Series. pp. 1173-1182, 21st ACM International Conference on Information and Knowledge Management, CIKM 2012, Maui, HI, United States, 29/10/12. https://doi.org/10.1145/2396761.2398417
Gao, Wei ; Li, Peng ; Darwish, Kareem. / Joint topic modeling for event summarization across news and social media streams. ACM International Conference Proceeding Series. 2012. pp. 1173-1182
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