TY - JOUR A1 - Frommholz, Ingo A1 - Haider M., al-Khateeb A1 - Potthast, Martin A1 - Ghasem, Zinnar A1 - Shukla, Mitul A1 - Short, Emma T1 - On Textual Analysis and Machine Learning for Cyberstalking Detection JF - Datenbank Spektrum N2 - Cyber security has become a major concern for users and businesses alike. Cyberstalking and harassment have been identified as a growing anti-social problem. Besides detecting cyberstalking and harassment, there is the need to gather digital evidence, often by the victim. To this end, we provide an overview of and discuss relevant technological means, in particular coming from text analytics as well as machine learning, that are capable to address the above challenges. We present a framework for the detection of text-based cyberstalking and the role and challenges of some core techniques such as author identification, text classification and personalisation. We then discuss PAN, a network and evaluation initiative that focusses on digital text forensics, in particular author identification. KW - Text Mining KW - Maschinelles Lernen Y1 - 2016 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20170418-31352 SP - 127 EP - 135 ER -