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International Journal of Advanced Computer Science and Applications(IJACSA), Volume 7 Issue 6, 2016.
Abstract: Online Social Network (OSN) is an online social platform that enables people to exchange information, get in touch with family members or friends, and also helps as a marketing tool. However, OSN suffers from various security and privacy issues. Trust, fundamentally, is made up of security with hard trust (cryptographic mechanism) and soft trust (recommender system); user's trustworthiness for this platform has decrement signed. In this paper, the authors leverage the multi-faceted model trust concept from user-centric and personalized trust model and present weightage and ranking for its important features by employing statistical means. Next, the multi-faceted model trust is combined with an existing Action-based model and Context recommender. The contributions of this research are an enhanced trust algorithm and an enhanced context-based, recommender-based trust, which has been tested based on user-acceptance. Overall, the result demonstrates OSN as fairly better by employing a multi-faceted model which embeds both actions incomparable to recommender type
Manmeet Mahinderjit Singh and Teo Yi Chin. “Hybrid Multi-faceted Computational Trust Model for Online Social Network (OSN)”. International Journal of Advanced Computer Science and Applications (IJACSA) 7.6 (2016). http://dx.doi.org/10.14569/IJACSA.2016.070601
@article{Singh2016,
title = {Hybrid Multi-faceted Computational Trust Model for Online Social Network (OSN)},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2016.070601},
url = {http://dx.doi.org/10.14569/IJACSA.2016.070601},
year = {2016},
publisher = {The Science and Information Organization},
volume = {7},
number = {6},
author = {Manmeet Mahinderjit Singh and Teo Yi Chin}
}
Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.