The dynamics of information dissemination in social networks is of paramount importance in processes such as rumors or fads propagation, spread of product innovations or "word-of-mouth" communications. Due to the difficulty in tracking a specific information when it is transmitted by people,...

We propose an agent-based computational model of a media market that consists of two connected levels: media voices reporting news and households forming a social network. To our knowledge, this is the first attempt to model news dissemination in large media markets, as our model accounts for...

We study an opinion formation game between a Designer and an Adversary. While the Designer creates the network, both these players can influence network nodes (agents) initially, with ties being broken in favor of the Designer. Final opinions of agents are a convex combination of own opinions...

I propose a social learning model that investigates how confirmatory bias affects public opinion when agents exchange information over a social network. For that, besides exchanging opinions with friends, individuals observe a public sequence of potentially ambiguous signals and they interpret...