<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>10</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Despoina Chatzakou</style></author><author><style face="normal" font="default" size="100%">Nicolas Kourtellis</style></author><author><style face="normal" font="default" size="100%">Jeremy Blackburn</style></author><author><style face="normal" font="default" size="100%">Emiliano De Cristofaro</style></author><author><style face="normal" font="default" size="100%">Gianluca Stringhini</style></author><author><style face="normal" font="default" size="100%">Athena Vakali</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Detecting Aggressors and Bullies on Twitter</style></title><secondary-title><style face="normal" font="default" size="100%">Proceedings of the 26th International Conference on World Wide Web Companion</style></secondary-title><tertiary-title><style face="normal" font="default" size="100%">WWW '17 Companion</style></tertiary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">crowdsourcing</style></keyword><keyword><style  face="normal" font="default" size="100%">cyber-aggression</style></keyword><keyword><style  face="normal" font="default" size="100%">cyberbullying</style></keyword><keyword><style  face="normal" font="default" size="100%">Twitter</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2017</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dl.acm.org/citation.cfm?id=3054211</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">ACM</style></publisher><pub-location><style face="normal" font="default" size="100%">Perth, Australia</style></pub-location><pages><style face="normal" font="default" size="100%">767--768</style></pages><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Online social networks constitute an integral part of people's every day social activity and the existence of aggressive and bullying phenomena in such spaces is inevitable. In this work, we analyze user behavior on Twitter in an effort to detect cyberbullies and cuber-aggressors by considering specific attributes of their online activity using machine learning classifiers.&lt;/p&gt;
</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Despoina Chatzakou</style></author><author><style face="normal" font="default" size="100%">Vassiliki A. Koutsonikola</style></author><author><style face="normal" font="default" size="100%">Athena Vakali</style></author><author><style face="normal" font="default" size="100%">Konstantinos Kafetsios</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Micro-blogging Content Analysis via Emotionally-Driven Clustering</style></title><secondary-title><style face="normal" font="default" size="100%">Affective Computing and Intelligent Interaction (ACII), 2013 Humaine Association Conference on</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">affective analysis methodology</style></keyword><keyword><style  face="normal" font="default" size="100%">Clustering algorithms</style></keyword><keyword><style  face="normal" font="default" size="100%">content management</style></keyword><keyword><style  face="normal" font="default" size="100%">content sharing</style></keyword><keyword><style  face="normal" font="default" size="100%">Dictionaries</style></keyword><keyword><style  face="normal" font="default" size="100%">emotion intensity monitoring</style></keyword><keyword><style  face="normal" font="default" size="100%">emotionally-driven clustering</style></keyword><keyword><style  face="normal" font="default" size="100%">Equations</style></keyword><keyword><style  face="normal" font="default" size="100%">human emotion states</style></keyword><keyword><style  face="normal" font="default" size="100%">information sharing</style></keyword><keyword><style  face="normal" font="default" size="100%">lexicon-based technique</style></keyword><keyword><style  face="normal" font="default" size="100%">Mathematical model</style></keyword><keyword><style  face="normal" font="default" size="100%">microblogging content analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">pattern clustering</style></keyword><keyword><style  face="normal" font="default" size="100%">people perception</style></keyword><keyword><style  face="normal" font="default" size="100%">Pragmatics</style></keyword><keyword><style  face="normal" font="default" size="100%">Semantics</style></keyword><keyword><style  face="normal" font="default" size="100%">Sentiment analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">social networking (online)</style></keyword><keyword><style  face="normal" font="default" size="100%">social pulse</style></keyword><keyword><style  face="normal" font="default" size="100%">social relations</style></keyword><keyword><style  face="normal" font="default" size="100%">text analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">Twitter</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2013</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Sept</style></date></pub-dates></dates><pages><style face="normal" font="default" size="100%">375-380</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record></records></xml>