On textual analysis and machine learning for cyberstalking detection
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AbstractCyber 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.
CitationFrommholz I, Al-Khateeb H, Potthast M, Ghasem Z, Shukla M, Short E (2016) 'On textual analysis and machine learning for cyberstalking detection', Datenbank-Spektrum : Zeitschrift fur Datenbanktechnologie : Organ der Fachgruppe Datenbanken der Gesellschaft fur Informatik e.V, 16 (2), pp.127-135.
JournalDatenbank-Spektrum : Zeitschrift fur Datenbanktechnologie : Organ der Fachgruppe Datenbanken der Gesellschaft fur Informatik e.V
PubMed Central IDPMC5750836
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- Creative Commons
Except where otherwise noted, this item's license is described as http://creativecommons.org/licenses/by-nc-nd/4.0/
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