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.…
Dokumentart: | Artikel (Wissenschaftlicher) |
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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): | Creative Commons 4.0 - Namensnennung (CC BY 4.0) |