Opinion modeling on social media and marketing aspects

Giuseppe Toscani, Andrea Tosin, Mattia Zanella

Physical Review E, 98(2): 022315, 2018. Preprint arXiv, 2018.

We introduce and discuss kinetic models of opinion formation on social networks in which the distribution function depends on both the opinion and the connectivity of the agents. The opinion formation model is subsequently coupled with a kinetic model describing the spreading of popularity of a product on the web through a social network. Numerical experiments on the underlying kinetic models show a good qualitative agreement with some measured trends of hashtags on social media websites and illustrate how companies can take advantage of the network structure to obtain at best the advertisement of their products.

Related popularization article for the Italian blog Madd:Math!: La popolarità delle opinioni



Opinion dynamics over complex networks: kinetic modelling and numerical methods


Giacomo Albi, Lorenzo Pareschi, Mattia Zanella

Kinetic and Related Models, 10(1): 1-32, 2017. Preprint arXiv.

In this paper we consider the modeling of opinion dynamics over time dependent large scale networks. A kinetic description of the agents’ distribution over the evolving network is considered which combines an opinion update based on binary interactions between agents with a dynamic creation and removal process of new connections. The number of connections of each agent influences the spreading of opinions in the network but also the way connections are created is influenced by the agents’ opinion. The evolution of the network of connections is studied by showing that its asymptotic behavior is consistent both with Poisson distributions and truncated power-laws. In order to study the large time behavior of the opinion dynamics a mean field description is derived which allows to compute exact stationary solutions in some simplified situations. Numerical methods which are capable to describe correctly the large time behavior of the system are also introduced and discussed. Finally, several numerical examples showing the influence of the agents’ number of connections in the opinion dynamics are reported.