On textual analysis and machine learning for cyberstalking detection
Abstract
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.Citation
Frommholz, I., al-Khateeb, H.M., Potthast, M. et al. Datenbank Spektrum (2016) 16: 127. https://doi.org/10.1007/s13222-016-0221-xPublisher
SpringerJournal
Datenbank-SpektrumAdditional Links
https://link.springer.com/article/10.1007/s13222-016-0221-xType
Journal articleLanguage
enISSN
1618-2162ae974a485f413a2113503eed53cd6c53
10.1007/s13222-016-0221-x
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