TweetMogaz v2

Identifying news stories in social media

Eslam Elsawy, Moamen Mokhtar, Walid Magdy

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

4 Citations (Scopus)

Abstract

TweetMogaz is a news portal platform that generates news reports from social media content. It uses an adaptive information filtering technique for tracking tweets relevant to news topics, such as politics and sports in some regions. Relevant tweets for each topic are used to generate a comprehensive report about public reaction toward events happening. Showing a news report about an entire topic may be suboptimal for some users, since users prefer story-oriented presentation. In this demonstration, we present a technique for identifying stories within a stream of microblogs on a given topic. Detected tweets on a news story are used to generate a dynamic pseudo-article that gets its content updated in real-time based on trends on Twitter. Pseudo-article consists of a title, front-page image, set of tweets on the story, and links to external news articles. The platform is running live and tracks news on hot topics including Egyptian politics, Syrian conflict, and international sports.

Original languageEnglish
Title of host publicationCIKM 2014 - Proceedings of the 2014 ACM International Conference on Information and Knowledge Management
PublisherAssociation for Computing Machinery, Inc
Pages2042-2044
Number of pages3
ISBN (Print)9781450325981
DOIs
Publication statusPublished - 3 Nov 2014
Event23rd ACM International Conference on Information and Knowledge Management, CIKM 2014 - Shanghai, China
Duration: 3 Nov 20147 Nov 2014

Other

Other23rd ACM International Conference on Information and Knowledge Management, CIKM 2014
CountryChina
CityShanghai
Period3/11/147/11/14

Fingerprint

Sports
Information filtering
Demonstrations
News
Social media

Keywords

  • Arabic
  • Clustering
  • Story detection
  • TweetMogaz
  • Twitter

ASJC Scopus subject areas

  • Information Systems and Management
  • Computer Science Applications
  • Information Systems

Cite this

Elsawy, E., Mokhtar, M., & Magdy, W. (2014). TweetMogaz v2: Identifying news stories in social media. In CIKM 2014 - Proceedings of the 2014 ACM International Conference on Information and Knowledge Management (pp. 2042-2044). Association for Computing Machinery, Inc. https://doi.org/10.1145/2661829.2661843

TweetMogaz v2 : Identifying news stories in social media. / Elsawy, Eslam; Mokhtar, Moamen; Magdy, Walid.

CIKM 2014 - Proceedings of the 2014 ACM International Conference on Information and Knowledge Management. Association for Computing Machinery, Inc, 2014. p. 2042-2044.

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

Elsawy, E, Mokhtar, M & Magdy, W 2014, TweetMogaz v2: Identifying news stories in social media. in CIKM 2014 - Proceedings of the 2014 ACM International Conference on Information and Knowledge Management. Association for Computing Machinery, Inc, pp. 2042-2044, 23rd ACM International Conference on Information and Knowledge Management, CIKM 2014, Shanghai, China, 3/11/14. https://doi.org/10.1145/2661829.2661843
Elsawy E, Mokhtar M, Magdy W. TweetMogaz v2: Identifying news stories in social media. In CIKM 2014 - Proceedings of the 2014 ACM International Conference on Information and Knowledge Management. Association for Computing Machinery, Inc. 2014. p. 2042-2044 https://doi.org/10.1145/2661829.2661843
Elsawy, Eslam ; Mokhtar, Moamen ; Magdy, Walid. / TweetMogaz v2 : Identifying news stories in social media. CIKM 2014 - Proceedings of the 2014 ACM International Conference on Information and Knowledge Management. Association for Computing Machinery, Inc, 2014. pp. 2042-2044
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