Thomas Friemel SONIC Speaker Series

Thomas FriemelThomas Friemel, Institute of Mass Communication and Media Research, University of Zurich “Impersonal Knowledge Networks of Public Opinion” Friday, May 14, 2010 presentation (audio and slides).

The concept of impersonal knowledge networks proposes a new approach for the study of political knowledge and public opinion. Factual knowledge questions and the analysis of simple frequency distributions provide only limited insights into the complex structures and dynamics of how people think and decide on political issues. The concept of impersonal knowledge networks proposes to understand public opinion as a network of topic related aspects. Free word associations of individuals are used as the basis to aggregate bigger knowledge networks. This aggregation is possible by transforming the two-mode network of respondents and their answers to a one mode network of topic aspects. Data presented in this talk were collected in representative CATI interviews on three different national referendum campaigns in Switzerland. The panel design allows not only to describe the knowledge structure at a given time point but also to analyze the dynamics of the structure.

Thomas N. Friemel is an Assistant Professor at the Institute of Mass Communication and Media Research at the University of Zurich (IPMZ) and currently Visiting Scholar at the Annenberg School for Communication at the University of Pennsylvania. He is the organizer of the annual conference on Applications of Social Network Analysis (ASNA) at the University of Zurich and ETH Zurich and applies SNA in various ways in mass communication research.


Impersonal Knowledge Networks of Public Opinion


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Mauro Cherubini SONIC Speaker Series

MauMauro Cherubiniro Cherubini, Telefonica Research, Barcelona, “Exploring Social Networks as an Infrastructure for Transportation Networks” Monday, May 10, 2010.

We propose an exchange platform where people lend each other objects of small value, such as star-shaped screwdrivers, which are transported by the owners or by carriers (friends or acquaintances of the owner in the social network). By running simulations on mobile call detail records, which include location information, from a large metropolitan area, we evaluate the performance of several transportation strategies. Results show that completely unoptimized routing heuristics could deliver an average of 3908 objects, over 10000 injected objects, with an average delivery time of 0.59 days. These preliminary results suggest that, under considerably general assumptions, social networks may indeed be an effective and inexpensive infrastructure for transportation networks. These initial results have important implications for sustainability.

Mauro Cherubini obtained a degree in Psychology and Education in 2001. He then worked at Media Lab Europe, in Ireland, with several study visits at MIT in Boston. In 2004, Mauro earned a Master of Arts by Research at Dublin City University. In 2008, he was conferred a PhD in Computer Science by the Swiss Federal Institute of Technology, where he conducted research on Human-Computer Interaction. In 2008, Mauro joined Telefonica Research, in Barcelona.

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Filip Agneessens SONIC Speaker Series

Filip AgneessFilip Agneessensens, VU University, Amsterdam “The importance of advice and trust on individual performance in teams: the effect of individual position in a network or group structure?” Friday, April 16th, 2010.

Both the way in which trust and advice relations influence the performance of employees in organizations, and the level at which these networks might have an impact on individual performance have been a major topic of discussion. This paper simultaneously investigates the impact of (1) trust as an independent effect next to advice, (2) trust as an underlying source for the emergence of advice, as well as (3) the importance of multiplex advice-trust ties for performance.  Moreover a multilevel analysis is used to simultaneously study the position of members in a team, and the impact of the structural characteristics of the team as a whole for individual performance. The results at the individual level show that the impact of frequent advice giving on performance is only partially mediated by the level to which the person is considered more trustworthy, while the effect of advice relations embedded in a trust-relation (i.e. advice-trust multiplexity) is not important. However, at the team level results show not only that a centralized advice structure (one, or a few persons being asked a lot for advice) and a decentralized trust network (members being more similar in the level they trust others) both have a positive effect on performance, but also that having more advice relations which are combined with trust in the team as a whole, have an impact on the performance of all its members.

Filip Agneessens’ research centers on network formation within organizations and their impact on attitudes and behavior of individual employees, with a particular focus on how networks might impact job satisfaction and performance. He has also been working on the development of random and biased networks, the building of social support typologies and how they might impact an individual’s wellbeing. In recent work he has also adapted exponential random graph models (p*models) to study cultural participation and (co) sponsorship among senators as two-mode networks. He teaches courses on network theory, social network methods and social network analysis applied to organizations.

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