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Towards Context-Aware Social Behavioral Analytics

Authors:

Vahid Moraveji Hashemi,

Shahpar YakhchiAuthors Info & Claims

MoMM2019: Proceedings of the 17th International Conference on Advances in Mobile Computing & Multimedia

Pages 28 - 35

https://doi.org/10.1145/3365921.3365942

Published: 22 February 2020 Publication History

Abstract

The confluence of technological and societal advances, and more specifically, engagement with Web, social media, and smart devices has the potential to affect the mental behavior of the individuals. Examples include extremist and criminal behaviors such as radicalization and cyber-bullying, which are causing serious issues for humanity. Major barriers to the effective understanding of behavioral disorders on social networks includes the ability to understand the content and context of social documents, as well as the activity of social users. Understanding the patterns of behavioral disorders (e.g., criminal and extremist activities) on social networks, is challenging and requires techniques to contextualize the content of social documents based on the time-aware analysis of personality, behaviour and past activities of social users. In this context, semantic information extraction and enrichment from social documents has the potential to become a vital asset to explore the sign of behavioral disorders and prevent serious issues such as cyber-bullying, suicidal related behavior and radicalization. To address this challenge, in this paper, we present a novel social document analysis pipeline to enable analysts engage with social documents (e.g., a Tweet in Twitter or a post on Facebook) to explore cognitive aspects of behavioral disorders. We implement the pipeline as an extensible and scalable architecture and present the evaluation results.

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Cited By

Rezvani NBeheshti AZhang X(2023)A Contextualized Transformer-Based Method for Cyberbullying Detection2023 IEEE 10th International Conference on Data Science and Advanced Analytics (DSAA)10.1109/DSAA60987.2023.10302478(1-10)Online publication date: 9-Oct-2023
https://doi.org/10.1109/DSAA60987.2023.10302478
Rezvani Nbeheshti ATabebordbar A(2020)Linking textual and contextual features for intelligent cyberbullying detection in social mediaProceedings of the 18th International Conference on Advances in Mobile Computing & Multimedia10.1145/3428690.3429171(3-10)Online publication date: 30-Nov-2020
https://dl.acm.org/doi/10.1145/3428690.3429171
Al-Obeidat FHani AAdedugbe OMajdalawieh MBenkhelifa E(2020)The Socio-economic Impacts of Social Media Privacy and Security ChallengesFrontiers in Cyber Security10.1007/978-981-15-9739-8_41(553-563)Online publication date: 4-Nov-2020
https://doi.org/10.1007/978-981-15-9739-8_41

Index Terms

Towards Context-Aware Social Behavioral Analytics

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MoMM2019: Proceedings of the 17th International Conference on Advances in Mobile Computing & Multimedia

December 2019

266 pages

ISBN:9781450371780

DOI:10.1145/3365921

Copyright © 2019 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Johannes Kepler University, Linz, Austria
@WAS: International Organization of Information Integration and Web-based Applications and Services

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 22 February 2020

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MoMM2019: The 17th International Conference on Advances in Mobile Computing & Multimedia

December 2 - 4, 2019

Munich, Germany

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Cited By

Rezvani NBeheshti AZhang X(2023)A Contextualized Transformer-Based Method for Cyberbullying Detection2023 IEEE 10th International Conference on Data Science and Advanced Analytics (DSAA)10.1109/DSAA60987.2023.10302478(1-10)Online publication date: 9-Oct-2023
https://doi.org/10.1109/DSAA60987.2023.10302478
Rezvani Nbeheshti ATabebordbar A(2020)Linking textual and contextual features for intelligent cyberbullying detection in social mediaProceedings of the 18th International Conference on Advances in Mobile Computing & Multimedia10.1145/3428690.3429171(3-10)Online publication date: 30-Nov-2020
https://dl.acm.org/doi/10.1145/3428690.3429171
Al-Obeidat FHani AAdedugbe OMajdalawieh MBenkhelifa E(2020)The Socio-economic Impacts of Social Media Privacy and Security ChallengesFrontiers in Cyber Security10.1007/978-981-15-9739-8_41(553-563)Online publication date: 4-Nov-2020
https://doi.org/10.1007/978-981-15-9739-8_41

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