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Link to original content: https://doi.org/10.1145/3366424.3385771

Temporal Properties of Cyberbullying on Instagram | Companion Proceedings of the Web Conference 2020

research-article

Temporal Properties of Cyberbullying on Instagram

Authors:

Divya Sivakumar,

Maria Nardini BarioniAuthors Info & Claims

WWW '20: Companion Proceedings of the Web Conference 2020

Pages 576 - 583

https://doi.org/10.1145/3366424.3385771

Published: 20 April 2020 Publication History

Abstract

Concurrent with the growth and widespread use of social networking platforms has been a rise in the prevalence of cyberbullying and cyberharassment, particularly among youth. Although cyberbullying is frequently defined as hostile communication or interactions that occur repetitively via electronic media, little is known about the temporal aspects of cyberbullying on social media, such as how the number, frequency, and timing of posts may vary systematically between cyberbullying and non-cyberbullying social media sessions. In this paper, we aim to contribute to the understanding of temporal properties of cyberbullying through the analysis of Instagram data. That is, the paper presents key temporal characteristics of cyberbullying and trends obtained from descriptive and burst analysis tasks. Our results have the potential to inform the development of more effective cyberbullying detection models.

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Cited By

Pathak VTripathi SKumar MPanigrahi SSohkey RKadian ABhattacharya MJha N(2024)Prevalence and factors associated with cyberbullying among adolescents (15–19 years) in Gurugram District – A community based cross-sectional studyIndian Journal of Psychiatry10.4103/indianjpsychiatry.indianjpsychiatry_867_2366:5(449-456)Online publication date: 20-May-2024
https://doi.org/10.4103/indianjpsychiatry.indianjpsychiatry_867_23
Zhou GLu XZhang RLiu HHuang B(2024)Time-User Heterogeneous Neural Interaction Network For Cyberbullying Detection2024 International Joint Conference on Neural Networks (IJCNN)10.1109/IJCNN60899.2024.10650684(1-8)Online publication date: 30-Jun-2024
https://doi.org/10.1109/IJCNN60899.2024.10650684
Ejaz NRazi FChoudhury S(2024)Towards comprehensive cyberbullying detection: A dataset incorporating aggressive texts, repetition, peerness, and intent to harmComputers in Human Behavior10.1016/j.chb.2023.108123153(108123)Online publication date: Apr-2024
https://doi.org/10.1016/j.chb.2023.108123
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Index Terms

Temporal Properties of Cyberbullying on Instagram

Index terms have been assigned to the content through auto-classification.

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Published In

cover image ACM Conferences

WWW '20: Companion Proceedings of the Web Conference 2020

April 2020

854 pages

ISBN:9781450370240

DOI:10.1145/3366424

Editors:
Amal El Fallah Seghrouchni
Sorbonne University, France
,
Gita Sukthankar
University of Central Florida, United States
,
Tie-Yan Liu
Microsoft Research Asia, China
,
Maarten van Steen
University of Twente, Netherlands

Copyright © 2020 ACM.

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Published: 20 April 2020

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Cited By

Pathak VTripathi SKumar MPanigrahi SSohkey RKadian ABhattacharya MJha N(2024)Prevalence and factors associated with cyberbullying among adolescents (15–19 years) in Gurugram District – A community based cross-sectional studyIndian Journal of Psychiatry10.4103/indianjpsychiatry.indianjpsychiatry_867_2366:5(449-456)Online publication date: 20-May-2024
https://doi.org/10.4103/indianjpsychiatry.indianjpsychiatry_867_23
Zhou GLu XZhang RLiu HHuang B(2024)Time-User Heterogeneous Neural Interaction Network For Cyberbullying Detection2024 International Joint Conference on Neural Networks (IJCNN)10.1109/IJCNN60899.2024.10650684(1-8)Online publication date: 30-Jun-2024
https://doi.org/10.1109/IJCNN60899.2024.10650684
Ejaz NRazi FChoudhury S(2024)Towards comprehensive cyberbullying detection: A dataset incorporating aggressive texts, repetition, peerness, and intent to harmComputers in Human Behavior10.1016/j.chb.2023.108123153(108123)Online publication date: Apr-2024
https://doi.org/10.1016/j.chb.2023.108123
López-Vizcaíno MNóvoa FArtieres TCacheda F(2023)Site Agnostic Approach to Early Detection of Cyberbullying on Social Media NetworksSensors10.3390/s2310478823:10(4788)Online publication date: 16-May-2023
https://doi.org/10.3390/s23104788
Lee LLi JKu STseng Y(2023)Filtering objectionable information access based on click-through behaviours with deep learning methodsJournal of Information Science10.1177/01655515231160041Online publication date: 7-Mar-2023
https://doi.org/10.1177/01655515231160041
Wang SZhu XDing WYengejeh A(2022)Cyberbullying and Cyberviolence Detection: A Triangular User-Activity-Content ViewIEEE/CAA Journal of Automatica Sinica10.1109/JAS.2022.1057409:8(1384-1405)Online publication date: Aug-2022
https://doi.org/10.1109/JAS.2022.105740
Cheng LGuo RSilva YHall DLiu H(2021)Modeling Temporal Patterns of Cyberbullying Detection with Hierarchical Attention NetworksACM/IMS Transactions on Data Science10.1145/34411412:2(1-23)Online publication date: 8-Apr-2021
https://dl.acm.org/doi/10.1145/3441141
Cheng LSilva YHall DLiu H(2021)Session-Based Cyberbullying Detection: Problems and ChallengesIEEE Internet Computing10.1109/MIC.2020.303293025:2(66-72)Online publication date: 1-Mar-2021
https://doi.org/10.1109/MIC.2020.3032930
Ferreira CMurai FSilva AAlmeida JTrevisan MVassio LMellia MDrago I(2021)On the dynamics of political discussions on Instagram: A network perspectiveOnline Social Networks and Media10.1016/j.osnem.2021.10015525(100155)Online publication date: Sep-2021
https://doi.org/10.1016/j.osnem.2021.100155
Hall DSilva YWheeler BCheng LBaumel K(2021)Harnessing the Power of Interdisciplinary Research with Psychology-Informed Cyberbullying Detection ModelsInternational Journal of Bullying Prevention10.1007/s42380-021-00107-54:1(47-54)Online publication date: 28-Oct-2021
https://doi.org/10.1007/s42380-021-00107-5
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