Sequential summarization: A new application for timely updated twitter trending topics

Dehong Gao, Wenjie Li, Renxian Zhang

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

12 Citations (Scopus)


The growth of the Web 2.0 technologies has led to an explosion of social networking media sites. Among them, Twitter is the most popular service by far due to its ease for realtime sharing of information. It collects millions of tweets per day and monitors what people are talking about in the trending topics updated timely. Then the question is how users can understand a topic in a short time when they are frustrated with the overwhelming and unorganized tweets. In this paper, this problem is approached by sequential summarization which aims to produce a sequential summary, i.e., a series of chronologically ordered short sub-summaries that collectively provide a full story about topic development. Both the number and the content of sub-summaries are automatically identified by the proposed stream-based and semantic-based approaches. These approaches are evaluated in terms of sequence coverage, sequence novelty and sequence correlation and the effectiveness of their combination is demonstrated.
Original languageEnglish
Title of host publicationShort Papers
PublisherAssociation for Computational Linguistics (ACL)
Number of pages5
ISBN (Print)9781937284510
Publication statusPublished - 1 Jan 2013
Event51st Annual Meeting of the Association for Computational Linguistics, ACL 2013 - Sofia, Bulgaria
Duration: 4 Aug 20139 Aug 2013


Conference51st Annual Meeting of the Association for Computational Linguistics, ACL 2013

ASJC Scopus subject areas

  • Language and Linguistics
  • Linguistics and Language

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