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A Survey on Trust Prediction in Online Social Networks

التفاصيل البيبلوغرافية
العنوان: A Survey on Trust Prediction in Online Social Networks
المؤلفون: Seyed Mohssen Ghafari, Amin Beheshti, Aditya Joshi, Cecile Paris, Adnan Mahmood, Shahpar Yakhchi, Mehmet A. Orgun
المصدر: IEEE Access, Vol 8, Pp 144292-144309 (2020)
بيانات النشر: IEEE, 2020.
سنة النشر: 2020
المجموعة: LCC:Electrical engineering. Electronics. Nuclear engineering
مصطلحات موضوعية: Context-aware, data sparsity problem, online social networks, pair-wise trust prediction, trust, trust relations, Electrical engineering. Electronics. Nuclear engineering, TK1-9971
الوصف: Level of Trust can determine which source of information is reliable and with whom we should share or from whom we should accept information. There are several applications for measuring trust in Online Social Networks (OSNs), including social spammer detection, fake news detection, retweet behaviour detection and recommender systems. Trust prediction is the process of predicting a new trust relation between two users who are not currently connected. In applications of trust, trust relations among users need to be predicted. This process faces many challenges, such as the sparsity of user-specified trust relations, the context-awareness of trust and changes in trust values over time. In this paper, we analyse the state-of-the-art in pair-wise trust prediction models in OSNs, classify them based on different factors, and propose some future directions for researchers interested in this field.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 2169-3536
10726195
Relation: https://ieeexplore.ieee.org/document/9142365/; https://doaj.org/toc/2169-3536
DOI: 10.1109/ACCESS.2020.3009445
URL الوصول: https://doaj.org/article/f9be1204e3b343a7b278eb10726195b2
رقم الأكسشن: edsdoj.f9be1204e3b343a7b278eb10726195b2
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:21693536
10726195
DOI:10.1109/ACCESS.2020.3009445