Community verification with topic modeling

Feng Wang, Ken Orton

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

Abstract

Different performance measurement metrics have been proposed to evaluate the performance of community detection algorithms, such as modularity, conductance, etc. However, there is few work which makes sense of a community, that is, explain what does the community do, what is the community’s interest. In this paper, we use topic modeling to capture the topics of users in the same community and verify a heuristic community detection algorithm by showing that the users in the communities share strong interests.

Original languageEnglish (US)
Title of host publicationWireless Algorithms, Systems, and Applications - 12th International Conference, WASA 2017, Proceedings
EditorsYan Zhang, Abdallah Khreishah, Mingyuan Yan, Liran Ma
PublisherSpringer Verlag
Pages278-288
Number of pages11
ISBN (Print)9783319600321
DOIs
StatePublished - 2017
Event12th International Conference on Wireless Algorithms, Systems, and Applications, WASA 2017 - Guilin, China
Duration: Jun 19 2017Jun 21 2017

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10251 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other12th International Conference on Wireless Algorithms, Systems, and Applications, WASA 2017
CountryChina
CityGuilin
Period6/19/176/21/17

Keywords

  • Community detection
  • LDA
  • Social media
  • Topic modeling

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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