Info-Trust: A Multi-Criteria and Adaptive Trustworthiness Calculation Mechanism for Information Sources

Social media have become increasingly popular for the sharing and spreading of user-generated content due to their easy access, fast dissemination, and low cost. Meanwhile, social media also enable the wide propagation of cyber frauds, which leverage fake information sources to reach an ulterior goal. The prevalence of untrustworthy information sources on social media can have significant negative societal effects. In a trustworthy social media system, trust calculation technology has become a key demand for the identification of information sources. Trust, as one of the most complex concepts in network communities, has multi-criteria properties. However, the existing work only focuses on single trust factor, and does not consider the complexity of trust relationships in social computing completely. In this paper, a multi-criteria trustworthiness calculation mechanism called Info-Trust is proposed for information sources, in which identity-based trust, behavior-based trust, relation-based trust, and feedback-based trust factors are incorporated to present an accuracy-enhanced full view of trustworthiness evaluation of information sources. More importantly, the weights of these factors are dynamically assigned by the ordered weighted averaging and weighted moving average (OWA-WMA) combination algorithm. This mechanism surpasses the limitations of existing approaches in which the weights are assigned subjectively. The experimental results based on the real-world datasets from Sina Weibo demonstrate that the proposed mechanism achieves greater accuracy and adaptability in trustworthiness identification of the network information.