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dc.contributor.authorNabipourshiri, R.
dc.contributor.authorAbu-Salih, B.
dc.contributor.authorWongthongtham, Pornpit
dc.identifier.citationNabipourshiri, R. and Abu-Salih, B. and Wongthongtham, P. 2018. Tree-based classification to users’ trustworthiness in OSNs, pp. 190-194.

© 2018 Association for Computing Machinery. In the light of the information revolution, and the propagation of big social data, the dissemination of misleading information is certainly difficult to control. This is due to the rapid and intensive flow of information through unconfirmed sources under the propaganda and tendentious rumors. This causes confusion, loss of trust between individuals and groups and even between governments and their citizens. This necessitates a consolidation of efforts to stop penetrating of false information through developing theoretical and practical methodologies aim to measure the credibility of users of these virtual platforms. This paper presents an approach to domain-based prediction to user’s trustworthiness of Online Social Networks (OSNs). Through incorporating three machine learning algorithms, the experimental results verify the applicability of the proposed approach to classify and predict domain-based trustworthy users of OSNs.

dc.titleTree-based classification to users’ trustworthiness in OSNs
dc.typeConference Paper
dcterms.source.titleACM International Conference Proceeding Series
dcterms.source.seriesACM International Conference Proceeding Series
curtin.departmentSustainability Policy Institute
curtin.accessStatusFulltext not available

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