TwitterNews+

A framework for real time event detection from the twitter data stream

Mahmud Hasan*, Mehmet A. Orgun, Rolf Schwitter

*Corresponding author for this work

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

14 Citations (Scopus)

Abstract

In recent years, substantial research efforts have gone into investigating different approaches to the detection of events in real time from the Twitter data stream. Most of these approaches, however, suffer from a high computational cost and are not evaluated using a publicly available corpus, thus making it difficult to properly compare them. In this paper, we propose a scalable event detection system, TwitterNews+, to detect and track newsworthy events in real time. TwitterNews+ uses a novel approach to cluster event related tweets from Twitter with a significantly lower computational cost compared to the existing state-of-theart approaches. Finally, we evaluate the effectiveness of TwitterNews+ using a publicly available corpus and its associated ground truth data set of newsworthy events. The result of the evaluation shows a significant improvement, in terms of recall and precision, over the baselines we have used.

Original languageEnglish
Title of host publicationSocial Informatics - 8th International Conference, SocInfo 2016, Proceedings
EditorsEmma Spiro, Yong-Yeol Ahn
Place of PublicationCham
PublisherSpringer, Springer Nature
Pages224-239
Number of pages16
Volume10046 LNCS
ISBN (Print)9783319478791
DOIs
Publication statusPublished - 2016
Event8th International Conference on Social Informatics, SocInfo 2016 - Bellevue, United States
Duration: 11 Nov 201614 Nov 2016

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10046 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other8th International Conference on Social Informatics, SocInfo 2016
CountryUnited States
CityBellevue
Period11/11/1614/11/16

Keywords

  • Event detection
  • Incremental clustering
  • Microblog
  • Social media
  • Twitter

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