iAnon: Leveraging Social Network Big Data to Mitigate Behavioral Symptoms of Cyberbullying

Ashktorab, Zahra; Kumar, Srijan; De, Soham; Golbeck, Jennifer

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https://hdl.handle.net/2142/48828 Copy

Description

Title

iAnon: Leveraging Social Network Big Data to Mitigate Behavioral Symptoms of Cyberbullying

Author(s)

• Ashktorab, Zahra
• Kumar, Srijan
• De, Soham
• Golbeck, Jennifer

Issue Date

2014-04-04

Keyword(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 ask.fm, 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 ask.fm 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.

Publisher

iSchools

Series/Report Name or Number

iConference 2014 (Social Media Expo)

Type of Resource

text

Language

en

Permalink

http://hdl.handle.net/2142/48828

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