Clustering users in micro blogging social networks using probabilistic topic modeling - A framework

Hossein Dolatabadi; Lay Ki Soon; Mahdi Negahi Shirazi; Mohammad Mohammadi

doi:10.1109/ICCSA.2012.28

Clustering users in micro blogging social networks using probabilistic topic modeling - A framework

Hossein Dolatabadi, Lay Ki Soon, Mahdi Negahi Shirazi, Mohammad Mohammadi

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review

1 Citation (Scopus)

Abstract

Social network is a term used to represent a large group of activities using the web and mobile technologies. The micro blogging social networks provide an appropriate ground for the users to explain themselves and express their ideas as well as interacting with the others. The growth of the social networks' users creates the necessity of extracting and analyzing the contents of the users' notes and multimedia products. In this paper, a new methodology is defined to characterize users based on the contents of their posts in micro blogging social networks and also to create clusters of users by means of highlighting the distribution of words representing a topic in the contents of micro blogging social networks.

Original language	English
Title of host publication	Proceedings - 12th International Conference on Computational Science and Its Applications, ICCSA 2012
Pages	113-116
Number of pages	4
DOIs	https://doi.org/10.1109/ICCSA.2012.28
Publication status	Published - 2012
Externally published	Yes
Event	International Conference on Computational Science and Applications 2012 - Salvador Bahia, Brazil Duration: 18 Jun 2012 → 21 Jun 2012 https://link.springer.com/book/10.1007/978-3-642-31125-3 (Proceedings)

Conference

Conference	International Conference on Computational Science and Applications 2012
Abbreviated title	ICCSA 2012
Country/Territory	Brazil
City	Salvador Bahia
Period	18/06/12 → 21/06/12
Internet address	https://link.springer.com/book/10.1007/978-3-642-31125-3 (Proceedings)

Keywords

Latent Dirichlet Allocation (LDA)
Micro blogging
Social network
Topic modeling algorithm
User clustering

Access to Document

10.1109/ICCSA.2012.28

Cite this

@inproceedings{7326cda159d44c2fab47d52e94d3d6b6,

title = "Clustering users in micro blogging social networks using probabilistic topic modeling - A framework",

abstract = "Social network is a term used to represent a large group of activities using the web and mobile technologies. The micro blogging social networks provide an appropriate ground for the users to explain themselves and express their ideas as well as interacting with the others. The growth of the social networks' users creates the necessity of extracting and analyzing the contents of the users' notes and multimedia products. In this paper, a new methodology is defined to characterize users based on the contents of their posts in micro blogging social networks and also to create clusters of users by means of highlighting the distribution of words representing a topic in the contents of micro blogging social networks.",

keywords = "Latent Dirichlet Allocation (LDA), Micro blogging, Social network, Topic modeling algorithm, User clustering",

author = "Hossein Dolatabadi and Soon, {Lay Ki} and Shirazi, {Mahdi Negahi} and Mohammad Mohammadi",

note = "Copyright: Copyright 2012 Elsevier B.V., All rights reserved.; International Conference on Computational Science and Applications 2012<br/>, ICCSA 2012 ; Conference date: 18-06-2012 Through 21-06-2012",

year = "2012",

doi = "10.1109/ICCSA.2012.28",

language = "English",

isbn = "9780769547107",

pages = "113--116",

booktitle = "Proceedings - 12th International Conference on Computational Science and Its Applications, ICCSA 2012",

url = "https://link.springer.com/book/10.1007/978-3-642-31125-3",

}

Dolatabadi, H, Soon, LK, Shirazi, MN & Mohammadi, M 2012, Clustering users in micro blogging social networks using probabilistic topic modeling - A framework. in Proceedings - 12th International Conference on Computational Science and Its Applications, ICCSA 2012. pp. 113-116, International Conference on Computational Science and Applications 2012
, Salvador Bahia, Brazil, 18/06/12. https://doi.org/10.1109/ICCSA.2012.28

Clustering users in micro blogging social networks using probabilistic topic modeling - A framework. / Dolatabadi, Hossein; Soon, Lay Ki; Shirazi, Mahdi Negahi et al.
Proceedings - 12th International Conference on Computational Science and Its Applications, ICCSA 2012. 2012. p. 113-116.

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review

TY - GEN

T1 - Clustering users in micro blogging social networks using probabilistic topic modeling - A framework

AU - Dolatabadi, Hossein

AU - Soon, Lay Ki

AU - Shirazi, Mahdi Negahi

AU - Mohammadi, Mohammad

PY - 2012

Y1 - 2012

N2 - Social network is a term used to represent a large group of activities using the web and mobile technologies. The micro blogging social networks provide an appropriate ground for the users to explain themselves and express their ideas as well as interacting with the others. The growth of the social networks' users creates the necessity of extracting and analyzing the contents of the users' notes and multimedia products. In this paper, a new methodology is defined to characterize users based on the contents of their posts in micro blogging social networks and also to create clusters of users by means of highlighting the distribution of words representing a topic in the contents of micro blogging social networks.

AB - Social network is a term used to represent a large group of activities using the web and mobile technologies. The micro blogging social networks provide an appropriate ground for the users to explain themselves and express their ideas as well as interacting with the others. The growth of the social networks' users creates the necessity of extracting and analyzing the contents of the users' notes and multimedia products. In this paper, a new methodology is defined to characterize users based on the contents of their posts in micro blogging social networks and also to create clusters of users by means of highlighting the distribution of words representing a topic in the contents of micro blogging social networks.

KW - Latent Dirichlet Allocation (LDA)

KW - Micro blogging

KW - Social network

KW - Topic modeling algorithm

KW - User clustering

UR - http://www.scopus.com/inward/record.url?scp=84866423149&partnerID=8YFLogxK

U2 - 10.1109/ICCSA.2012.28

DO - 10.1109/ICCSA.2012.28

M3 - Conference Paper

AN - SCOPUS:84866423149

SN - 9780769547107

SP - 113

EP - 116

BT - Proceedings - 12th International Conference on Computational Science and Its Applications, ICCSA 2012

T2 - International Conference on Computational Science and Applications 2012<br/>

Y2 - 18 June 2012 through 21 June 2012

ER -

Clustering users in micro blogging social networks using probabilistic topic modeling - A framework

Abstract

Conference

Keywords

Access to Document

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