Multi-view Community Detection in Facebook Public Pages

Zhige Xin; Chun Ming Lai; Jon W. Chapman; George Barnett; S. Felix Wu

doi:10.1007/978-981-13-9190-3_12

Multi-view Community Detection in Facebook Public Pages

Zhige Xin, Chun Ming Lai, Jon W. Chapman, George Barnett, S. Felix Wu

Department of Electrical Engineering

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

Abstract

Community detection in social networks is widely studied because of its importance in uncovering how people connect and interact. However, little attention has been given to community structure in Facebook public pages. In this study, we investigate the community detection problem in Facebook newsgroup pages. In particular, to deal with the diversity of user activities, we apply multi-view clustering to integrate different views, for example, likes on posts and likes on comments. In this study, we explore the community structure in Facebook public pages. The results show that our method can effectively reduce isolates and improve the quality of community structure.

Original language	English
Title of host publication	New Trends in Computer Technologies and Applications - 23rd International Computer Symposium, ICS 2018, Revised Selected Papers
Editors	Chuan-Yu Chang, Chien-Chou Lin, Horng-Horng Lin
Publisher	Springer Verlag
Pages	131-138
Number of pages	8
ISBN (Print)	9789811391897
DOIs	https://doi.org/10.1007/978-981-13-9190-3_12
Publication status	Published - 2019
Event	23rd International Computer Symposium, ICS 2018 - Yunlin, Taiwan Duration: 2018 Dec 20 → 2018 Dec 22

Publication series

Name	Communications in Computer and Information Science
Volume	1013
ISSN (Print)	1865-0929
ISSN (Electronic)	1865-0937

Conference

Conference	23rd International Computer Symposium, ICS 2018
Country/Territory	Taiwan
City	Yunlin
Period	18-12-20 → 18-12-22

All Science Journal Classification (ASJC) codes

General Computer Science
General Mathematics

Access to Document

10.1007/978-981-13-9190-3_12

Cite this

Xin, Z., Lai, C. M., Chapman, J. W., Barnett, G., & Wu, S. F. (2019). Multi-view Community Detection in Facebook Public Pages. In C.-Y. Chang, C.-C. Lin, & H.-H. Lin (Eds.), New Trends in Computer Technologies and Applications - 23rd International Computer Symposium, ICS 2018, Revised Selected Papers (pp. 131-138). (Communications in Computer and Information Science; Vol. 1013). Springer Verlag. https://doi.org/10.1007/978-981-13-9190-3_12

Xin, Zhige ; Lai, Chun Ming ; Chapman, Jon W. et al. / Multi-view Community Detection in Facebook Public Pages. New Trends in Computer Technologies and Applications - 23rd International Computer Symposium, ICS 2018, Revised Selected Papers. editor / Chuan-Yu Chang ; Chien-Chou Lin ; Horng-Horng Lin. Springer Verlag, 2019. pp. 131-138 (Communications in Computer and Information Science).

@inproceedings{39f56c99c6c747e49b866ca7e119feb5,

title = "Multi-view Community Detection in Facebook Public Pages",

abstract = "Community detection in social networks is widely studied because of its importance in uncovering how people connect and interact. However, little attention has been given to community structure in Facebook public pages. In this study, we investigate the community detection problem in Facebook newsgroup pages. In particular, to deal with the diversity of user activities, we apply multi-view clustering to integrate different views, for example, likes on posts and likes on comments. In this study, we explore the community structure in Facebook public pages. The results show that our method can effectively reduce isolates and improve the quality of community structure.",

author = "Zhige Xin and Lai, {Chun Ming} and Chapman, {Jon W.} and George Barnett and Wu, {S. Felix}",

note = "Publisher Copyright: {\textcopyright} Springer Nature Singapore Pte Ltd. 2019.; 23rd International Computer Symposium, ICS 2018 ; Conference date: 20-12-2018 Through 22-12-2018",

year = "2019",

doi = "10.1007/978-981-13-9190-3_12",

language = "English",

isbn = "9789811391897",

series = "Communications in Computer and Information Science",

publisher = "Springer Verlag",

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booktitle = "New Trends in Computer Technologies and Applications - 23rd International Computer Symposium, ICS 2018, Revised Selected Papers",

address = "Germany",

}

Xin, Z, Lai, CM, Chapman, JW, Barnett, G & Wu, SF 2019, Multi-view Community Detection in Facebook Public Pages. in C-Y Chang, C-C Lin & H-H Lin (eds), New Trends in Computer Technologies and Applications - 23rd International Computer Symposium, ICS 2018, Revised Selected Papers. Communications in Computer and Information Science, vol. 1013, Springer Verlag, pp. 131-138, 23rd International Computer Symposium, ICS 2018, Yunlin, Taiwan, 18-12-20. https://doi.org/10.1007/978-981-13-9190-3_12

Multi-view Community Detection in Facebook Public Pages. / Xin, Zhige; Lai, Chun Ming; Chapman, Jon W. et al.
New Trends in Computer Technologies and Applications - 23rd International Computer Symposium, ICS 2018, Revised Selected Papers. ed. / Chuan-Yu Chang; Chien-Chou Lin; Horng-Horng Lin. Springer Verlag, 2019. p. 131-138 (Communications in Computer and Information Science; Vol. 1013).

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

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T1 - Multi-view Community Detection in Facebook Public Pages

AU - Xin, Zhige

AU - Lai, Chun Ming

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N1 - Publisher Copyright: © Springer Nature Singapore Pte Ltd. 2019.

PY - 2019

Y1 - 2019

N2 - Community detection in social networks is widely studied because of its importance in uncovering how people connect and interact. However, little attention has been given to community structure in Facebook public pages. In this study, we investigate the community detection problem in Facebook newsgroup pages. In particular, to deal with the diversity of user activities, we apply multi-view clustering to integrate different views, for example, likes on posts and likes on comments. In this study, we explore the community structure in Facebook public pages. The results show that our method can effectively reduce isolates and improve the quality of community structure.

AB - Community detection in social networks is widely studied because of its importance in uncovering how people connect and interact. However, little attention has been given to community structure in Facebook public pages. In this study, we investigate the community detection problem in Facebook newsgroup pages. In particular, to deal with the diversity of user activities, we apply multi-view clustering to integrate different views, for example, likes on posts and likes on comments. In this study, we explore the community structure in Facebook public pages. The results show that our method can effectively reduce isolates and improve the quality of community structure.

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T3 - Communications in Computer and Information Science

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BT - New Trends in Computer Technologies and Applications - 23rd International Computer Symposium, ICS 2018, Revised Selected Papers

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Xin Z, Lai CM, Chapman JW, Barnett G, Wu SF. Multi-view Community Detection in Facebook Public Pages. In Chang CY, Lin CC, Lin HH, editors, New Trends in Computer Technologies and Applications - 23rd International Computer Symposium, ICS 2018, Revised Selected Papers. Springer Verlag. 2019. p. 131-138. (Communications in Computer and Information Science). doi: 10.1007/978-981-13-9190-3_12

Multi-view Community Detection in Facebook Public Pages

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