By now people’s opinions and actions are more and more strongly influenced by what is posted and shared on the various social networks. Thus, malicious users can purposely manipulate other users posting fake news/reviews. In order to face this challenge, modern online social networks are beginning to adopt tool for user trustworthiness assessment. Current assessment solutions mainly adopt multi-criteria frameworks for user trustworthiness assessment but fail at properly dealing with uncertainty and vagueness in computed/collected scores and aggregating them in a robust manner. In this paper, we propose a larger set of criteria than existing related works, and the use of subjective logic to represent and combine subjective and objective scores. Specifically, several of assessment criteria are introduced for verifying user trust from different point of views (usefulness and quality of user reviews, users’ influence/importance in terms of activities and centrality within the social network, time dependent crown consensus investigating aspect-based sentiments and opinions of reviews w.r.t. the majority), aiming at improving accuracy and precision in trust estimation. The available fusion operators in the literature of subjective logic have been compared so as to find the best one fitting the needs of trust estimation. The proposed solution has been implemented and evaluated against public Yelp data-sets so as to prove its effectiveness and efficiency w.r.t. existing related works within the literature.

现在，人们的意见和行动越来越受到在各种社交网络上发布和分享的内容的强烈影响。因此，恶意用户可以故意操纵发布虚假新闻/评论的其他用户。为了应对这一挑战，现代在线社交网络开始采用用户可信度评估工具。当前的评估解决方案主要采用多标准框架进行用户可信度评估，但未能妥善处理计算/收集分数中的不确定性和模糊性，并以稳健的方式对其进行汇总。在本文中，我们提出了一套比现有相关作品更大的标准，并使用主观逻辑来表示和结合主观和客观分数。具体来说，引入了几个评估标准来从不同的角度验证用户信任（用户评论的有用性和质量，用户在活动和社交网络中的中心性方面的影响/重要性，时间相关的皇冠共识调查基于方面的情绪和意见评论占大多数），旨在提高信任估计的准确性和精确度。已经比较了主观逻辑文献中可用的融合算子，以找到最适合信任估计需求的融合算子。提议的解决方案已针对公共 Yelp 数据集实施和评估，以证明其有效性和效率与文献中现有的相关工作相比。用户在社交网络中的活动和中心性方面的影响/重要性，时间相关的皇冠共识调查基于方面的情绪和评论意见占大多数），旨在提高信任估计的准确性和精确度。比较了主观逻辑文献中可用的融合算子，以找到最适合信任估计需求的融合算子。提议的解决方案已针对公共 Yelp 数据集实施和评估，以证明其有效性和效率与文献中现有的相关工作相比。用户在社交网络中的活动和中心性方面的影响/重要性，时间相关的皇冠共识调查基于方面的情绪和评论意见占大多数），旨在提高信任估计的准确性和精确度。已经比较了主观逻辑文献中可用的融合算子，以找到最适合信任估计需求的融合算子。提议的解决方案已针对公共 Yelp 数据集实施和评估，以证明其有效性和效率与文献中现有的相关工作相比。比较了主观逻辑文献中可用的融合算子，以找到最适合信任估计需求的融合算子。提议的解决方案已针对公共 Yelp 数据集实施和评估，以证明其有效性和效率与文献中现有的相关工作相比。比较了主观逻辑文献中可用的融合算子，以找到最适合信任估计需求的融合算子。提议的解决方案已针对公共 Yelp 数据集实施和评估，以证明其有效性和效率与文献中现有的相关工作相比。