A framework for early detection of antisocial behavior on Twitter using natural language processing

Ravinder Singh, Jiahua Du, Yanchun Zhang, Hua Wang, Yuan Miao, Omid Ameri Sianaki, Anwaar Ul-Haq

Research output: Book chapter/Published conference paperConference paper

Abstract

Online antisocial behavior is a social problem and a public health threat. A manifestation of such behavior may be fun for a perpetrator, however, can drive a victim into depression, self-confinement, low self-esteem, anxiety,anger, and suicidal ideation. Online platforms such as Twitter and Facebook can sometimes become breeding grounds for such behavior. These platforms may have measures in place to deter online antisocial behavior, however, such behavior still prevails. Most of the measures rely on users reporting to platforms for intervention. In this paper, we advocate a more proactive approach based on natural language processing and machine learning that can enable online platforms to actively look for signs of antisocial behavior and intervene before it gets out of control. By actively searching for such behavior, social media sites can possibly prevent dire situations that can lead to someone committing suicide.
Original languageEnglish
Title of host publicationComplex, Intelligent, and Software Intensive Systems
Subtitle of host publicationProceedings of the 13th International Conference on Complex, Intelligent, and Software Intensive Systems (CISIS-2019)
EditorsLeonard Barolli, Farookh Khadeer Hussain, Makoto Ikeda
Place of PublicationSwitzerland
PublisherSpringer Nature
Pages484-495
Number of pages12
Volume993
ISBN (Electronic)9783030223540
ISBN (Print)9783030223533
Publication statusPublished - 21 Jun 2019
Event13th International Conference on Complex, Intelligent, and Software Intensive Systems : CISIS 2019 - University of Sydney, Sydney, Australia
Duration: 03 Jul 201905 Jul 2019
http://voyager.ce.fit.ac.jp/conf/cisis/2019/index.php

Publication series

NameAdvances in Intelligent Systems and Computing
Volume993

Conference

Conference13th International Conference on Complex, Intelligent, and Software Intensive Systems
CountryAustralia
CitySydney
Period03/07/1905/07/19
Internet address

Fingerprint

Public health
Learning systems
Processing

Cite this

Singh, R., Du, J., Zhang, Y., Wang, H., Miao, Y., Ameri Sianaki, O., & Ul-Haq, A. (2019). A framework for early detection of antisocial behavior on Twitter using natural language processing. In L. Barolli, F. Khadeer Hussain, & M. Ikeda (Eds.), Complex, Intelligent, and Software Intensive Systems: Proceedings of the 13th International Conference on Complex, Intelligent, and Software Intensive Systems (CISIS-2019) (Vol. 993, pp. 484-495). (Advances in Intelligent Systems and Computing; Vol. 993). Switzerland: Springer Nature.
Singh, Ravinder ; Du, Jiahua ; Zhang, Yanchun ; Wang, Hua ; Miao, Yuan ; Ameri Sianaki, Omid ; Ul-Haq, Anwaar. / A framework for early detection of antisocial behavior on Twitter using natural language processing. Complex, Intelligent, and Software Intensive Systems: Proceedings of the 13th International Conference on Complex, Intelligent, and Software Intensive Systems (CISIS-2019). editor / Leonard Barolli ; Farookh Khadeer Hussain ; Makoto Ikeda. Vol. 993 Switzerland : Springer Nature, 2019. pp. 484-495 (Advances in Intelligent Systems and Computing).
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title = "A framework for early detection of antisocial behavior on Twitter using natural language processing",
abstract = "Online antisocial behavior is a social problem and a public health threat. A manifestation of such behavior may be fun for a perpetrator, however, can drive a victim into depression, self-confinement, low self-esteem, anxiety,anger, and suicidal ideation. Online platforms such as Twitter and Facebook can sometimes become breeding grounds for such behavior. These platforms may have measures in place to deter online antisocial behavior, however, such behavior still prevails. Most of the measures rely on users reporting to platforms for intervention. In this paper, we advocate a more proactive approach based on natural language processing and machine learning that can enable online platforms to actively look for signs of antisocial behavior and intervene before it gets out of control. By actively searching for such behavior, social media sites can possibly prevent dire situations that can lead to someone committing suicide.",
author = "Ravinder Singh and Jiahua Du and Yanchun Zhang and Hua Wang and Yuan Miao and {Ameri Sianaki}, Omid and Anwaar Ul-Haq",
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Singh, R, Du, J, Zhang, Y, Wang, H, Miao, Y, Ameri Sianaki, O & Ul-Haq, A 2019, A framework for early detection of antisocial behavior on Twitter using natural language processing. in L Barolli, F Khadeer Hussain & M Ikeda (eds), Complex, Intelligent, and Software Intensive Systems: Proceedings of the 13th International Conference on Complex, Intelligent, and Software Intensive Systems (CISIS-2019). vol. 993, Advances in Intelligent Systems and Computing, vol. 993, Springer Nature, Switzerland, pp. 484-495, 13th International Conference on Complex, Intelligent, and Software Intensive Systems , Sydney, Australia, 03/07/19.

A framework for early detection of antisocial behavior on Twitter using natural language processing. / Singh, Ravinder; Du, Jiahua; Zhang, Yanchun; Wang, Hua; Miao, Yuan; Ameri Sianaki, Omid; Ul-Haq, Anwaar.

Complex, Intelligent, and Software Intensive Systems: Proceedings of the 13th International Conference on Complex, Intelligent, and Software Intensive Systems (CISIS-2019). ed. / Leonard Barolli; Farookh Khadeer Hussain; Makoto Ikeda. Vol. 993 Switzerland : Springer Nature, 2019. p. 484-495 (Advances in Intelligent Systems and Computing; Vol. 993).

Research output: Book chapter/Published conference paperConference paper

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Singh R, Du J, Zhang Y, Wang H, Miao Y, Ameri Sianaki O et al. A framework for early detection of antisocial behavior on Twitter using natural language processing. In Barolli L, Khadeer Hussain F, Ikeda M, editors, Complex, Intelligent, and Software Intensive Systems: Proceedings of the 13th International Conference on Complex, Intelligent, and Software Intensive Systems (CISIS-2019). Vol. 993. Switzerland: Springer Nature. 2019. p. 484-495. (Advances in Intelligent Systems and Computing).