Location-based emerging event detection in social networks

Sayan Unankard, Xue Li, Mohamed A. Sharaf

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

9 Citations (Scopus)

Abstract

This paper proposes a system for the early detection of emerging events by grouping micro-blog messages into events and using the message-mentioned locations to identify the locations of events. In our research we correlate user locations with event locations in order to identify the strong correlations between locations and events that are emerging. We have evaluated our approach on a real-world Twitter dataset with different granularity of location levels. Our experiments show that the proposed approach can effectively detect the top-k ranked emerging events with respect to the locations of the users in the different granularity of location scales.

Original languageEnglish
Title of host publicationWeb Technologies and Applications - 15th Asia-Pacific Web Conference, APWeb 2013, Proceedings
Pages280-291
Number of pages12
DOIs
Publication statusPublished - 2013
Externally publishedYes
Event15th Asia-Pacific Web Conference on Web Technologies and Applications, APWeb 2013 - Sydney, NSW, Australia
Duration: Apr 4 2013Apr 6 2013

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7808 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference15th Asia-Pacific Web Conference on Web Technologies and Applications, APWeb 2013
Country/TerritoryAustralia
CitySydney, NSW
Period4/4/134/6/13

Keywords

  • Emerging event detection
  • Location-based social networks
  • Micro-blogs

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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