MID-ToRS

In social networks, users choose to connect (“follow”) an influencer if the messages he sends seem relevant to them. For each “follower”, the quality of information is based on the distance between the message and a pre-established belief, making it specific to each individual and evolving over time. Thus, a social influencer, to increase his connectivity degree in the interaction graph, can behave strategically by choosing the messages he sends, based on his own anticipation of the beliefs of other users. Conversely, an influencer with a high connectivity degree has an impact on the overall belief present on the network. In this project, based on the framework of game theory in networks, we study the optimal strategy of the influencer in terms of sending messages (nature, frequency). We also address the question that arises for the network administrator or public authority: how to measure the relative weight of influencers in the evolution of the overall belief, and how to protect followers from the creation of information bubbles, that is to say how can one influence the influencers so as to maintain plurality of opinions in the network?