TY - GEN
T1 - Towards User Modelling in the Combat Against Cyberbullying
AU - Dadvar, M.
AU - Ordelman, Roeland J.F.
AU - de Jong, Franciska M.G.
AU - Trieschnigg, Rudolf Berend
N1 - 10.1007/978-3-642-31178-9_34
PY - 2012/6
Y1 - 2012/6
N2 - Friendships, relationships and social communications have all gone to a new level with new definitions as a result of the invention of online social networks. Meanwhile, alongside this transition there is increasing evidence that online social applications have been used by children and adolescents for bullying. State-of-the-art studies in cyberbullying detection have mainly focused on the content of the conversations while largely ignoring the users involved in cyberbullying. We hypothesis that incorporation of the users’ profile, their characteristics, and post-harassing behaviour, for instance, posting a new status in another social network as a reaction to their bullying experience, will improve the accuracy of cyberbullying detection. Cross-system analyses of the users’ behaviour - monitoring users’ reactions in different online environments - can facilitate this process and could lead to more accurate detection of cyberbullying. This paper outlines the framework for this faceted approach.
AB - Friendships, relationships and social communications have all gone to a new level with new definitions as a result of the invention of online social networks. Meanwhile, alongside this transition there is increasing evidence that online social applications have been used by children and adolescents for bullying. State-of-the-art studies in cyberbullying detection have mainly focused on the content of the conversations while largely ignoring the users involved in cyberbullying. We hypothesis that incorporation of the users’ profile, their characteristics, and post-harassing behaviour, for instance, posting a new status in another social network as a reaction to their bullying experience, will improve the accuracy of cyberbullying detection. Cross-system analyses of the users’ behaviour - monitoring users’ reactions in different online environments - can facilitate this process and could lead to more accurate detection of cyberbullying. This paper outlines the framework for this faceted approach.
KW - METIS-287902
KW - IR-80708
KW - User Profile
KW - HMI-MR: MULTIMEDIA RETRIEVAL
KW - Cyberbullying Detection
KW - EWI-21995
KW - Harassment Detection
U2 - 10.1007/978-3-642-31178-9_34
DO - 10.1007/978-3-642-31178-9_34
M3 - Conference contribution
SN - 978-3-642-31177-2
T3 - Lecture Notes in Computer Science
SP - 277
EP - 283
BT - Proceedings of the17th International Conference on Applications of Natural Language to Information Systems, NLDB 2012
PB - Springer
CY - Berlin
T2 - Proceedings of the17th International Conference on Applications of Natural Language to Information Systems, NLDB 2012
Y2 - 26 June 2012 through 28 June 2012
ER -