Careful what you share in six seconds: detecting cyberbullying instances in Vine

Rahat Ibn Rafiq, Homa Hosseinmardi, Richard Han, Qin Lv, Shivakant Mishra, Sabrina Arredondo Mattson

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionpeer-review

43 Citations (Scopus)

Abstract

As online social networks have grown in popularity, teenage users have become increasingly exposed to the threats of cyberbullying. The primary goal of this research paper is to investigate cyberbullying behaviors in Vine, a mobile based video-sharing online social network, and design novel approaches to automatically detect instances of cyberbullying over Vine media sessions. We first collect a set of Vine video sessions and use CrowdFlower, a crowd-sourced website, to label the media sessions for cyberbullying and cyberaggression. We then perform a detailed analysis of cyberbullying behavior in Vine. Based on the labeled data, we design a classifier to detect instances of cyberbullying and evaluate the performance of that classifier.

Original languageEnglish
Title of host publicationProceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2015
EditorsJian Pei, Jie Tang, Fabrizio Silvestri
Place of PublicationNew York, NY
PublisherAssociation for Computing Machinery (ACM)
Pages617-622
Number of pages6
ISBN (Electronic)9781450338547
DOIs
Publication statusPublished - 2015
Externally publishedYes
EventIEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2015 - Paris, France
Duration: 25 Aug 201528 Aug 2015

Publication series

NameProceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2015

Conference

ConferenceIEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2015
CountryFrance
CityParis
Period25/08/1528/08/15

Fingerprint Dive into the research topics of 'Careful what you share in six seconds: detecting cyberbullying instances in Vine'. Together they form a unique fingerprint.

Cite this