The paper explores the use of concepts in cognitive psychology to evaluate the spread of misinformation, disinformation and propaganda in online social networks. Analysing online social networks to identify metrics to infer cues of deception will enable us to measure diffusion of misinformation. The cognitive process involved in the decision to spread information involves answering four main questions viz consistency of message, coherency of message, credibility of source and general acceptability of message. We have used the cues of deception to analyse these questions to obtain solutions for preventing the spread of misinformation. We have proposed an algorithm to effectively detect deliberate spread of false information which would enable users to make informed decisions while spreading information in social networks. The computationally efficient algorithm uses the collaborative filtering property of social networks to measure the credibility of sources of information as well as quality of news items. The validation of the proposed methodology has been done on the online social network 'Twitter'.

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With the advent of Web 2.0, social networks have become an important medium for dissemination of information in the Internet. The process of information dissemination in social networks has been studied using a number of information diffusion models. Due to the collaborative nature of the networks and limited accountability of the users, the media is often misused for spread of rumours and misinformation. In this paper, we have a proposed a novel information diffusion model for the spread of misinformation using Evolutionary game theory and Evolutionary graph theory. The proposed model could be used to analyse as well as predict the spread of misinformation. It also provides a framework to study the effects of multiple campaigns in the network which would enable us to estimate the efficacy of launching counter campaigns against the spread of misinformation. We have used extensive simulation to support our claim.