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Title:iAnon: Leveraging Social Network Big Data to Mitigate Behavioral Symptoms of Cyberbullying
Author(s):Ashktorab, Zahra; Kumar, Srijan; De, Soham; Golbeck, Jennifer
Subject(s):social networks
interface design
cyberbullying mitigation
Abstract:Because of the widespread use of social networks, it is difficult for victims of cyberbullying to seek refuge from this torment of bullying. Some social networking sites, like, enable abusive behavior by allowing users to send public messages to one another anonymously. Under the guise of anonymity, users of these services can send abusive messages to one another without being accountable for their actions. This abusive behavior has real world consequences.In this paper, we introduce iAnon, a tool that aims to support victims of cyberbullying by providing anonymous support through their social networks. iAnon automatically detects users who are at risk and allows third party ”do-gooders” to anonymously send friendly encouraging messages to victims. We hope that our tool, iAnon, can help mitigate feelings of depression and loneliness that are often felt by victims of cyberbullying by providing an online support system for cyberbullying victims.
Issue Date:2014-04-04
Citation Info:Ashktorab, Z.; Kumar, S.; De, S.; Golbeck S. (2014). iAnon: Leveraging Social Network Big Data to Mitigate Behavioral Symptoms of Cyberbullying. In iConference 204 (Social Media Expo)
Series/Report:iConference 2014 (Social Media Expo)
Genre:Conference Paper / Presentation
Publication Status:published or submitted for publication
Peer Reviewed:is peer reviewed
Date Available in IDEALS:2014-04-07

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