Mitchell Centre seminar series
|Dates:||23 February 2022|
|Times:||16:00 - 17:00|
|What is it:||Seminar|
|Organiser:||School of Social Sciences|
Statistical modeling of social groups: An example and some outlooks
Many social relations are situated within groups. Social groups are formed, for example, when students decide with whom to carry out their group assignments, when researchers collaborate on the writing of scientific papers, or when citizens join different political parties. Although many theories acknowledge the importance of groups to explain social outcomes, we currently lack statistical tools to explain the existence and composition of these groups.
Existing network models rely on dyadic representations of social relations and can only represent social groups as two-mode ties or node attributes. An important limitation of such approaches is that they do not allow the modeling of coordination processes between all members of a group simultaneously but generally assume a successive creation of dyadic ties. They also often require modelers to define the groups in advance, while there are often no theoretical reasons to expect a priori a certain number of groups.
Recent work on higher-order links and hypergraphs shows, however, that this gap can be bridged. This talk will first review the challenges associated with models for social groups and current solutions to them. It will then present our recent contribution to this literature, a statistical model tailored for non-overlapping groups inspired by previous models for social ties such as the ERGM. Finally, this model will be used to discuss the specification of group models more generally and the theoretical concerns they raise.
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