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Networks, Culture, and Action - Workshops and Seminar

An event of the Competence Area "Social and Economic Behavior" of the University of Cologne

Organisation: Prof. Dr. Clemens Kroneberg
Institute of Sociology and Social Psychology

In sociology, social network analysis ("relational turn") and cultural sociology ("cultural turn") have developed into booming research fields in recent years. However, the intersection of these areas has been relatively sparsely populated, not least due to the primarily quantitative orientation of network scholars and the primarily hermeneutic-ethnographic tradition of cultural sociology. At the same time, current work at this intersection has been extraordinarily innovative and visible. In this workshop series and seminar, we will focus particularly on the integration of action-theoretic and network-analytic approaches. Substantively, the question is how social relations form between individuals and how these networks in turn influence their beliefs and decisions.

The seminar is organized around two workshops, financed and supported by Competence Area "Social and Economic Behavior" of the University of Cologne. These workshops will bring worldwide leading scholars to Cologne who will discuss their recent work with each other as well as with participants of the public talks and workshops.

Upcoming workshop "Networks, Culture, and Action II", November 28 and 29, 2018:

PART 1: Public talks
Wednesday, Nov 28, 16:00-17:30

Location: 106 Seminarraum S01 (106/EG/0.02)

Mario Luis Small (Harvard University): Understanding Personal Networks: On the Limits of Big Data and the Perils of Common Sense.

When people seek emotional support, how do they decide whom to talk to? Network analysis and common sense would both suggest that people will go to those they are closest to-their strong ties. Based on in-depth interviews with graduate students in one university and nationally representative survey data on adults 18 and older, Small finds reason to question that belief. Shifting from what people say to what they actually do, Small shows that widely-agreed upon assumptions about the nature of strong ties do not stand up to qualitative empirical scrutiny-do not accord with how people in their ordinary lives interact with those they are close to. The findings will suggest that, in big data era, qualitative research has become more, not less important to social science.

Tom A.B. Snijders (University of Groningen, University of Oxford): Modeling Network Dynamics - What does it Teach Us about Social Reality?

The Stochastic Actor-oriented Model for network dynamics is based on quite specific assumptions. Which role do these play for opening up, and limiting, applications? The mathematical assumptions of a model are not the assumptions necessary for applying it. To have some understanding of the role of assumptions in statistical methodology, we first discuss the role of the well-known assumptions in the linear regression model. Armed with this background, the assumptions of the Stochastic Actor-oriented Model are considered: an unobserved process in continuous time, changes of one variable at a time, changes organized by actors, specific probabilities for these changes. These mathematical assumptions, however, come close to implying a variety of other assumptions of a more methodological nature, such as a proper network delineation, error-free observation of ties, and - perhaps - an assumption of complete information. 'Come close to' is not a concept known in logical reasoning, and indeed here the discussion starts to be of the slippery kind that is inevitable when transitioning between the questions posed in social science and the toolbox of statistics. I shall try to present the main epistemological assumptions underlying the use of the Stochastic Actor-oriented Model, relevant for an empirical-theoretical researcher. All assumptions in methodology are used as approximations, and I shall discuss my view on their sensitivity from a practical point of view.

PART 2: Internal seminar
Thursday, Nov 29, 10:00-13:30

Location: TBA

Previous workshop "Networks, Culture, and Action I", September 26 and 27, 2018:

PART 1: Public talks
Wednesday, Sept 26, 16:00-17:30

Stephen Vaisey (Duke University): Theory and Time: How Past and Present Environments Affect Cultural Change

How does social influence happen over time? Classical theories in sociology emphasized early life socialization whereas more contemporary theories emphasize local network influence and the ongoing fluidity of "meaning making." Understanding how social influence works is a crucial part of any general approach to sociological theory. Using data from several sources, the author investigates patterns of change over time and their relevance for adjudicating between (and integrating) competing theoretical models.  

Achim Edelmann (University of Bern): Boundaries, Networks, and Drinking: How Symbolic Boundaries Moderate Social Influence

In this paper, I propose and test a new model of peer influence to analyze how cultural forms can mediate social influence. Peer influence is a fundamental process in social life. Network scientists generally conceptualize influence as an additive process, with increasing exposure to others’ behavior or attitudes associated with a greater likelihood of adopting them. Based on cognitive theories of symbolic boundaries, I propose an alternative model that regards peer influence as conditional on membership in the same symbolic group. I test this model with data from a large, nationally-representative dataset. I use a counterfactual logic and instrumental variable methods to estimate peer influence on adolescent drinking. I find that, for religious adolescents, having a same-religion friend who drinks is more strongly predictive of drinking behavior than exposure to drinking and same-religion friends alone. For some behaviors, peer influence should not be understood simply as a function of exposure, but also of the violation of symbolic group boundaries.

PART 2: Internal seminar
Thursday, Sept 27, 10:00-13:30