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On Textual Analysis and Machine Learning for Cyberstalking Detection

  • 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 asCyber 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.zeige mehrzeige weniger

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Metadaten
Dokumentart:Artikel (Wissenschaftlicher)
Verfasserangaben: Ingo Frommholz, al-Khateeb Haider M., Martin PotthastGND, Zinnar Ghasem, Mitul Shukla, Emma Short
DOI (Zitierlink):https://doi.org/10.1007/s13222-016-0221-xZitierlink
URN (Zitierlink):https://nbn-resolving.org/urn:nbn:de:gbv:wim2-20170418-31352Zitierlink
Titel des übergeordneten Werkes (Englisch):Datenbank Spektrum
Sprache:Englisch
Datum der Veröffentlichung (online):18.04.2017
Jahr der Erstveröffentlichung:2016
Datum der Freischaltung:18.04.2017
Veröffentlichende Institution:Bauhaus-Universität Weimar
Institute und Partnereinrichtugen:Bauhaus-Universität Weimar / In Zusammenarbeit mit der Bauhaus-Universität Weimar
Erste Seite:127
Letzte Seite:135
GND-Schlagwort:Text Mining; Maschinelles Lernen
DDC-Klassifikation:000 Informatik, Informationswissenschaft, allgemeine Werke / 000 Informatik, Wissen, Systeme
BKL-Klassifikation:54 Informatik / 54.38 Computersicherheit
Lizenz (Deutsch):License Logo Creative Commons 4.0 - Namensnennung (CC BY 4.0)