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BullyAlert- A Mobile Application for Adaptive Cyberbullying Detection

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Mobile Computing, Applications, and Services (MobiCASE 2020)

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Abstract

Due to the prevalence and severe consequences of cyberbullying, numerous research works have focused on mining and analyzing social network data to understand cyberbullying behavior and then using the gathered insights to develop accurate classifiers to detect cyberbullying. Some recent works have been proposed to leverage the detection classifiers in a centralized cyberbullying detection system and send notifications to the concerned authority whenever a person is perceived to be victimized. However, two concerns limit the effectiveness of a centralized cyberbullying detection system. First, a centralized detection system gives a uniform severity level of alerts to everyone, even though individual guardians might have different tolerance levels when it comes to what constitutes cyberbullying. Second, the volume of data being generated by old and new social media makes it computationally prohibitive for a centralized cyberbullying detection system to be a viable solution. In this work, we propose BullyAlert, an android mobile application for guardians that allows the computations to be delegated to the hand-held devices. In addition to that, we incorporate an adaptive classification mechanism to accommodate the dynamic tolerance level of guardians when receiving cyberbullying alerts. Finally, we include a preliminary user analysis of guardians and monitored users using the data collected from BullyAlert usage.

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Authors and Affiliations

  1. University of Colorado Boulder, Boulder, CO, USA

    Rahat Ibn Rafiq, Richard Han, Qin Lv & Shivakant Mishra

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  1. Rahat Ibn Rafiq
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  2. Richard Han
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  4. Shivakant Mishra
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Correspondence to Rahat Ibn Rafiq .

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Editors and Affiliations

  1. East China Normal University, Shanghai, China

    Jing Liu

  2. Shanghai University, Shanghai, China

    Honghao Gao

  3. College of Computer, Hangzhou Dianzi University, Hangzhou, China

    Yuyu Yin

  4. Shanghai University of Electric Power, Shanghai, China

    Zhongqin Bi

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© 2020 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Rafiq, R.I., Han, R., Lv, Q., Mishra, S. (2020). BullyAlert- A Mobile Application for Adaptive Cyberbullying Detection. In: Liu, J., Gao, H., Yin, Y., Bi, Z. (eds) Mobile Computing, Applications, and Services. MobiCASE 2020. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 341. Springer, Cham. https://doi.org/10.1007/978-3-030-64214-3_1

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  • DOI: https://doi.org/10.1007/978-3-030-64214-3_1

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