From the 20th of February until the 1st of March I will be travelling around the UK to have some presentations, meetings, and academic visits.

• 21.02.2024. Presentation (1) at The Mitchell Centre for Social Network Analysis, The University of Manchester (host: Tomáš Diviák)

• 22.02.2024. Visit the Exeter Centre for Social Networks, University of Exeter (host: Stefano Tasselli)

• 26.02.2024. [Cancelled] Visit the Department of Sociology and the Institute for Social and Economic Research (ISER), University of Essex (host: Zsófia Boda)

• 26.02.2024 - 28.02.2024. Presentation (1) and academic visit to the School of Social Policy, University of Birmingham (host: András Vörös)

• 29.02.2024. Presentation (2) at Oxford Internet Institute, Oxford University (host: Bernie Hogans) and an academic visit to colleagues at Nuffield College, Oxford University (host: Pablo Geraldo)

• 01.03.2024. Presentation (2) at Networks and Urban Systems Centre, University of Greenwich (host: Bruce Cronin)

Presentation 1

Title: Identification and structural composition of informal groups

Authors: Alejandro Espinosa-Rada (Social Networks Lab, ETH Zürich), András Vörös (University of Birmingham), Christoph Stadtfeld (Social Networks Lab, ETH Zürich)

Abstract: The study of informal groups has been a relevant topic in social science to investigate the importance of social identities, the disposition toward collective action, or the formation of local norms and meanings (Lindenberg, 1997; Fine, 2012). Most studies using a social network perspective concentrate on identifying common social categories (Tajfel et al., 1971; Turner et al., 1987; Hogg et al., 1995) or identifying inductively cohesive subgroups (Alba, 1981; Freeman, 2003; Girvan & Newman, 2002) to understand groups. However, less is known about how actors identify with specific informal groups and how groups differ in their structural composition. The following article aims to understand why students identify with informal groups and how different these groups are. To explore potential explanations of the identification of actors toward informal groups, we consider the relevance and characteristics of different focus of activities, the composition of the perceived ego networks, and the similarity among sociodemographic attributes of the actors. Likewise, we distinguished between groups according to the main sociodemographic characteristics to identify the structures of the groups. We develop this argument using longitudinal network data of students' perceptions of informal groups' belongingness (The Swiss StudentLife Study; Vörös et al., 2021). Using this longitudinal design of the third cohort of the study (N=660), we asked students about the informal social groups in the cohort that they felt they belonged to and to mention peers in their cohort with whom they perceived to be the members of these informal groups. Each actor was asked about the level of identification with the group for each group mentioned. We used network autocorrelation models (e.g., Ord, 1975; Doreian, 1980, 1981; Leenders, 2002) for the exploratory analysis. Our main results indicate that some social activities are more relevant for social identification than others. The similarity in attributes and composition of the networks is likewise relevant to distinguish whether the actors identify more with these groups. Hence, to explore cohesive subgroups, further research should distinguish the relevance of some of the focus of activities and the group's composition to understand group formation.

Presentation 2

Title: Co-evolution of a socio-cognitive scientific network: A case study of citation dynamics among astronomers. 

Authors: Alejandro Espinosa-Rada (Social Networks Lab, ETH Zürich), Elisa Bellotti (The Mitchell Centre for Social Network Analysis, The University of Manchester), Martin G. Everett (The Mitchell Centre for Social Network Analysis, The University of Manchester), Christoph Stadtfeld (Social Networks Lab, ETH Zürich)

Abstract: This paper aims to understand how a group of academics cite each others’ work through time, considering the simultaneous co-evolution of three networks representing their scientific collaboration, the journals in which they publish and institutional membership. It argues that both social and cognitive processes contribute to these dynamics. Two types of network mechanisms are considered specifically: closures by affiliation and closures by association. To assess whether these mechanisms generate the macro features of the network under study, we propose new features for three-mode multilevel networks such as the mixed geodesic distances, mixed degree distributions, and the mixed quadrilateral census. We investigate whether a micro-level model that considers the above-mentioned network mechanisms is able to correctly reproduce these features. We apply stochastic actor-oriented models (SAOMs) for one-mode and two-mode networks to link the micro-macro processes using a dataset of a scientific community of astronomers from 2013 to 2015. The results suggest that social relationships grounded on scientific collaboration and proximity based on institutional affiliation are more accurately suited to understanding the co-evolution of the network of citations than an alternative approach that merely considers cognitive-based networks measured as the similarity in publishing in the same journals.