Show Abstract
Establishing a solid mechanism for finding credible and trustworthy people in online social networks is an important first step to avoid useless, misleading or even malicious information. Social network users can hide their intention or fabricate their virtual personality to gain trust of others. There is a body of existing work studying trustworthiness of social media users and finding credible sources in specific target domains. However, most of the related work lack the connection between the credibility in the real-world and credibility on the Internet, which makes the formation of social media credibility and trustworthiness incomplete. In this paper, working in the financial domain, we identify attributes that can distinguish credible users on the Internet who are indeed trustworthy experts in the real-world. To ensure objectivity, we gather the list of credible financial experts from real-world financial authorities. By analyzing the distribution of attributes of social media users using the random forest classifier, we can find which attributes are related to real-world expertise, and which attributes have higher potential of being forged by malicious users.
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