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Topic: Information spread on social networks under time and memory constraints.
Abstract: The spread of information on social networks is an important topic of research and there exist a large number of model approaches to capture the corresponding dynamics. Information spread on networks is related and can also be seen in the wider context of social contagion processes and opinion formation models. In the simplest setting one can consider information spread on networks as an epidemic process where a transmission happens with a certain probability p along a contact represented by an edge in the network. In this setting the general wisdom is, that as more edges a network has, the larger the number of individuals having the information becomes and the faster an information spread takes place. Taking into account time or memory constraints changes this picture since the likelihood of transmission should be proportional to the time spent within a contact and as more contacts a person has as smaller the share of time attributed to a contact with one of its neighbors becomes. In consequence it is no longer true that more edges automatically enhance the spread of information. In the talk we discuss some mathematical and numerical results on the spread of information for various network topologies and highlight the importance to take time and memory constraints into account when modelling information spread on networks in a semi realistic fashion.
Dr Jan Schneider (ZN1) opowie nam o współpracy z Panem Profesorem.
