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Entropy Based Identification of Fake Profiles in Social Network: An Application of Cyberbullying

Entropy Based Identification of Fake Profiles in Social Network: An Application of Cyberbullying

Geetika Sarna, M.P.S. Bhatia
Copyright: © 2017 |Volume: 9 |Issue: 4 |Pages: 13
ISSN: 1942-9010|EISSN: 1942-9029|EISBN13: 9781522512622|DOI: 10.4018/IJVCSN.2017100102
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MLA

Sarna, Geetika, and M.P.S. Bhatia. "Entropy Based Identification of Fake Profiles in Social Network: An Application of Cyberbullying." IJVCSN vol.9, no.4 2017: pp.18-30. http://doi.org/10.4018/IJVCSN.2017100102

APA

Sarna, G. & Bhatia, M. (2017). Entropy Based Identification of Fake Profiles in Social Network: An Application of Cyberbullying. International Journal of Virtual Communities and Social Networking (IJVCSN), 9(4), 18-30. http://doi.org/10.4018/IJVCSN.2017100102

Chicago

Sarna, Geetika, and M.P.S. Bhatia. "Entropy Based Identification of Fake Profiles in Social Network: An Application of Cyberbullying," International Journal of Virtual Communities and Social Networking (IJVCSN) 9, no.4: 18-30. http://doi.org/10.4018/IJVCSN.2017100102

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Abstract

Cyberbullying is a felonious act carried out against the victim by sending harassing/ embarrassing/ abusing information online. Normally offenders create fake profiles in order to hide their identity for unscrupulous activities. Assuming a fake identity is very harmful as the real picture of the offender is not visible, and also it can become difficult to entrap them. Sometimes, some trustworthy friends can also take advantage of the fake identity in order to harm the victim. Culprits can reveal victim's personal information like financial details, personal history, family, etc., and along with it, he can harass, threaten or blackmail the victim using fake profiles and permeates that information on the social network. So, it is necessary to resolve this issue. In this article, the authors used the concept of entropy and cross entropy to identify fake profiles as entropy works on the degree of uncertainty. Also, this article shows the comparison of proposed method with the existing classifiers.

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