Opportunistic content dissemination in mobile social networks via adjustment of user selfishness

Abstract

By increase in smart phone penetration rate, mobile social networks (MSNs) become more popular. In such networks, users can exchange and share information via peer-to-peer opportunistic wireless connections. Wireless connections are prone to failures, devices are battery-powered, and the buffer space is limited. These lead to uncertainty in connections and selfish behaviours in dissemination processes. Hence, information dissemination in MSNs becomes a challenge. In this study, the authors analyse the information dissemination in MSNs with selfish users from different communities. They develop an analytical model through ordinary differential equations to analyse the dissemination process in MSNs. Then, they propose an optimisation problem to find the optimal forwarding probabilities of users. They employ the branch and bound-outer approximation algorithm to analytically solve the optimisation problem. The analytical results represent that the optimal forwarding probability of users diminished by increasing the number of relay users, which accelerate the dissemination in the network. Also, these results represent that the proposed algorithm to find the optimal selfishness vector can improve the network performance by decreasing the dissemination delay.

Fuzzy‐based fake information detection algorithm to define the user trust on the content of social networks

“…The membership function on set A, µA is defined as in (8). The membership function over the Z items is defined in (9) and the details of the function that tends to the item are given in (10).…”

“…Ranging from trending news to contacting customer services, people have started to seek information through social media platforms [8][9][10]. In addition to the real-time capabilities, the easy access provision of social media acts as an added advantage for users [4,[11][12][13].…”