Towards understanding cyberbullying behavior in a semi-anonymous social network

Homa Hosseinmardi; Richard Han; Qin Lv; Shivakant Mishra; Amir Ghasemianlangroodi

doi:10.1109/ASONAM.2014.6921591

Towards understanding cyberbullying behavior in a semi-anonymous social network

Homa Hosseinmardi, Richard Han, Qin Lv, Shivakant Mishra, Amir Ghasemianlangroodi

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

51 Citations (Scopus)

Abstract

Cyberbullying has emerged as an important and growing social problem, wherein people use online social networks and mobile phones to bully victims with offensive text, images, audio and video on a 24/7 basis. This paper studies negative user behavior in the Ask.fm social network, a popular new site that has led to many cases of cyberbullying, some leading to suicidal behavior.We examine the occurrence of negative words in Ask.fm's question+answer profiles along with the social network of 'likes' of questions+answers. We also examine properties of users with 'cutting' behavior in this social network.

Original language	English
Title of host publication	ASONAM 2014 - Proceedings of the 2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
Editors	Martin Ester, Guandong Xu, Xindong Wu, Xindong Wu
Place of Publication	Piscataway, NJ
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Pages	244-252
Number of pages	9
ISBN (Electronic)	9781479958771, 9781479958764
DOIs	https://doi.org/10.1109/ASONAM.2014.6921591
Publication status	Published - 2014
Externally published	Yes
Event	2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2014 - Beijing, China Duration: 17 Aug 2014 → 20 Aug 2014

Publication series

Name	ASONAM 2014 - Proceedings of the 2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining

Other

Other	2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2014
Country/Territory	China
City	Beijing
Period	17/08/14 → 20/08/14

Bibliographical note

Publisher Copyright:
© 2014 IEEE.

Copyright:
Copyright 2014 Elsevier B.V., All rights reserved.

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10.1109/ASONAM.2014.6921591

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Hosseinmardi, H., Han, R., Lv, Q., Mishra, S., & Ghasemianlangroodi, A. (2014). Towards understanding cyberbullying behavior in a semi-anonymous social network. In M. Ester, G. Xu, X. Wu, & X. Wu (Eds.), ASONAM 2014 - Proceedings of the 2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (pp. 244-252). (ASONAM 2014 - Proceedings of the 2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining). Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/ASONAM.2014.6921591

Hosseinmardi, Homa ; Han, Richard ; Lv, Qin ; Mishra, Shivakant ; Ghasemianlangroodi, Amir. / Towards understanding cyberbullying behavior in a semi-anonymous social network. ASONAM 2014 - Proceedings of the 2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining. editor / Martin Ester ; Guandong Xu ; Xindong Wu ; Xindong Wu. Piscataway, NJ : Institute of Electrical and Electronics Engineers (IEEE), 2014. pp. 244-252 (ASONAM 2014 - Proceedings of the 2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining).

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title = "Towards understanding cyberbullying behavior in a semi-anonymous social network",

abstract = "Cyberbullying has emerged as an important and growing social problem, wherein people use online social networks and mobile phones to bully victims with offensive text, images, audio and video on a 24/7 basis. This paper studies negative user behavior in the Ask.fm social network, a popular new site that has led to many cases of cyberbullying, some leading to suicidal behavior.We examine the occurrence of negative words in Ask.fm's question+answer profiles along with the social network of 'likes' of questions+answers. We also examine properties of users with 'cutting' behavior in this social network.",

author = "Homa Hosseinmardi and Richard Han and Qin Lv and Shivakant Mishra and Amir Ghasemianlangroodi",

note = "Publisher Copyright: {\textcopyright} 2014 IEEE. Copyright: Copyright 2014 Elsevier B.V., All rights reserved.; 2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2014 ; Conference date: 17-08-2014 Through 20-08-2014",

year = "2014",

doi = "10.1109/ASONAM.2014.6921591",

language = "English",

series = "ASONAM 2014 - Proceedings of the 2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining",

publisher = "Institute of Electrical and Electronics Engineers (IEEE)",

pages = "244--252",

editor = "Martin Ester and Guandong Xu and Xindong Wu and Xindong Wu",

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address = "United States",

}

Hosseinmardi, H, Han, R, Lv, Q, Mishra, S & Ghasemianlangroodi, A 2014, Towards understanding cyberbullying behavior in a semi-anonymous social network. in M Ester, G Xu, X Wu & X Wu (eds), ASONAM 2014 - Proceedings of the 2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining. ASONAM 2014 - Proceedings of the 2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, Institute of Electrical and Electronics Engineers (IEEE), Piscataway, NJ , pp. 244-252, 2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2014, Beijing, China, 17/08/14. https://doi.org/10.1109/ASONAM.2014.6921591

Towards understanding cyberbullying behavior in a semi-anonymous social network. / Hosseinmardi, Homa; Han, Richard; Lv, Qin; Mishra, Shivakant; Ghasemianlangroodi, Amir.

ASONAM 2014 - Proceedings of the 2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining. ed. / Martin Ester; Guandong Xu; Xindong Wu; Xindong Wu. Piscataway, NJ : Institute of Electrical and Electronics Engineers (IEEE), 2014. p. 244-252 (ASONAM 2014 - Proceedings of the 2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining).

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

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AB - Cyberbullying has emerged as an important and growing social problem, wherein people use online social networks and mobile phones to bully victims with offensive text, images, audio and video on a 24/7 basis. This paper studies negative user behavior in the Ask.fm social network, a popular new site that has led to many cases of cyberbullying, some leading to suicidal behavior.We examine the occurrence of negative words in Ask.fm's question+answer profiles along with the social network of 'likes' of questions+answers. We also examine properties of users with 'cutting' behavior in this social network.

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Hosseinmardi H, Han R, Lv Q, Mishra S, Ghasemianlangroodi A. Towards understanding cyberbullying behavior in a semi-anonymous social network. In Ester M, Xu G, Wu X, Wu X, editors, ASONAM 2014 - Proceedings of the 2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining. Piscataway, NJ : Institute of Electrical and Electronics Engineers (IEEE). 2014. p. 244-252. (ASONAM 2014 - Proceedings of the 2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining). https://doi.org/10.1109/ASONAM.2014.6921591

Towards understanding cyberbullying behavior in a semi-anonymous social network

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