Analyzing the multiple facets of cyber-aggression on social media
Speaker: Nicolas Kourtellis, Telefonica Research
Date: 27 March 2018 Time: 12:00
Location: Room 1
Host: Evangelos Markatos


In recent years, offensive, abusive and hateful language, sexism,  racism and other types of aggressive and cyberbullying behavior have  been manifesting with increased frequency, and in many online social  media platforms. In fact, past scientific work focused on studying  these forms in popular media, such as Facebook, Twitter, Instagram,  Ask.fm, etc. However, these platforms have not adequately addressed  the problem of online abusive behavior, and their responsiveness, as  well as effective detection and blocking of such inappropriate  behavior remain limited. In this talk, I will cover our recent works,  in which we propose a set of algorithms to detect and mitigate such  complex user behavior. In these studies, we collect, analyze and  annotate user content from Twitter, and employ advanced machine and  deep learning approaches to detect online aggressive behavior, in its  various facets. We use a diverse set of features, extracted from  textual, user and network-related activities of Twitter users, and  demonstrate that such characteristics can boost the algorithmic  performance for detection cyber-aggression. Furthermore, we make our  collected and annotated datasets and algorithms publicly available for  further research and development by the scientific community. This  research has been supported by the Marie Sklodowska Curie RISE EU  project, No 691025.


Dr. Nicolas Kourtellis is a Researcher in the Telefonica R&D team, in  Barcelona. Previously he was a Postdoctoral Researcher in the Web  Mining Research Group at Yahoo Labs, in Barcelona. He holds a Ph.D. in  Computer Science and Engineering from the University of South Florida  (2012), a MSc in Computer Science from the University of South Florida  (2008), and a BSc in Electrical and Computer Engineering from the  National Technical University of Athens, Greece (2006). His primary  interests lie (1) in the analysis and characterization of online user  behavior, with respect to different dimensions such as: abusive,  hateful, aggressive and bullying behavior, fake news propagation,  fringe online communities, etc., (2) user online privacy, leakage of  personal data to the online advertising ecosystem, (3) system design  for load balancing of distributed streaming processing engines and  streaming graph analysis. He has published more than 40 papers, and  presented his work in top academic conferences and journals such as  IEEE TKDE, IEEE TPDS, IEEE ICDE, ACM KDD, ACM WWW, ACM/IFIP/USENIX  Middleware, ACM IMC, etc., as well as industry-oriented conferences  such as Apache BigData in Europe and N. America. He has served in many  program committees of top conferences and journals (e.g., WWW, KDD,  CIKM, ACM TKDD, IEEE TKDE, IEEE TPDS, etc.).

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