Community verification with topic modeling

Feng Wang; Ken Orton

doi:10.1007/978-3-319-60033-8_25

Community verification with topic modeling

Feng Wang, Ken Orton

Mathematical and Natural Sciences, School of (SMNS)

Research output: Chapter in Book/Report/Conference proceeding › Conference 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 language	English (US)
Title of host publication	Wireless Algorithms, Systems, and Applications - 12th International Conference, WASA 2017, Proceedings
Editors	Yan Zhang, Abdallah Khreishah, Mingyuan Yan, Liran Ma
Publisher	Springer Verlag
Pages	278-288
Number of pages	11
ISBN (Print)	9783319600321
DOIs	https://doi.org/10.1007/978-3-319-60033-8_25
State	Published - 2017
Event	12th International Conference on Wireless Algorithms, Systems, and Applications, WASA 2017 - Guilin, China Duration: Jun 19 2017 → Jun 21 2017

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	10251 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Other

Other	12th International Conference on Wireless Algorithms, Systems, and Applications, WASA 2017
Country/Territory	China
City	Guilin
Period	6/19/17 → 6/21/17

Keywords

Community detection
LDA
Social media
Topic modeling

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

Access to Document

10.1007/978-3-319-60033-8_25

Cite this

Wang, F., & Orton, K. (2017). Community verification with topic modeling. In Y. Zhang, A. Khreishah, M. Yan, & L. Ma (Eds.), Wireless Algorithms, Systems, and Applications - 12th International Conference, WASA 2017, Proceedings (pp. 278-288). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10251 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-319-60033-8_25

Community verification with topic modeling. / Wang, Feng; Orton, Ken.
Wireless Algorithms, Systems, and Applications - 12th International Conference, WASA 2017, Proceedings. ed. / Yan Zhang; Abdallah Khreishah; Mingyuan Yan; Liran Ma. Springer Verlag, 2017. p. 278-288 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10251 LNCS).

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

Wang, F & Orton, K 2017, Community verification with topic modeling. in Y Zhang, A Khreishah, M Yan & L Ma (eds), Wireless Algorithms, Systems, and Applications - 12th International Conference, WASA 2017, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 10251 LNCS, Springer Verlag, pp. 278-288, 12th International Conference on Wireless Algorithms, Systems, and Applications, WASA 2017, Guilin, China, 6/19/17. https://doi.org/10.1007/978-3-319-60033-8_25

Wang F, Orton K. Community verification with topic modeling. In Zhang Y, Khreishah A, Yan M, Ma L, editors, Wireless Algorithms, Systems, and Applications - 12th International Conference, WASA 2017, Proceedings. Springer Verlag. 2017. p. 278-288. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-60033-8_25

Wang, Feng ; Orton, Ken. / Community verification with topic modeling. Wireless Algorithms, Systems, and Applications - 12th International Conference, WASA 2017, Proceedings. editor / Yan Zhang ; Abdallah Khreishah ; Mingyuan Yan ; Liran Ma. Springer Verlag, 2017. pp. 278-288 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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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{\textquoteright}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.",

keywords = "Community detection, LDA, Social media, Topic modeling",

author = "Feng Wang and Ken Orton",

note = "Funding Information: This project is supported by NSF grant CNS #1218212. Publisher Copyright: {\textcopyright} Springer International Publishing AG 2017.; 12th International Conference on Wireless Algorithms, Systems, and Applications, WASA 2017 ; Conference date: 19-06-2017 Through 21-06-2017",

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Community verification with topic modeling

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Keywords

ASJC Scopus subject areas

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