SNAC 2008 PAPERS

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Network of inter-relationships in Mathematics using the concept of Cognitive Mobility

Basu, Aparna  (CSIR, New Delhi)

 Wagner-Doebler, Roland (University of Augsburg)

  

Abstract: Cognitive mobility is a concept describing migration of researchers into other fields/subfields. It is recognized as an important ingredient in the transfer of new knowledge into fields, some prominent examples being physicist Max Delbruck who initiated the field of molecular biology and mathematician John von Neumann who moved to economics. Often these migrations have led to scientific breakthroughs. Interesting insights may be gained into the structure of a discipline by mapping the entire landscape of migrations, rather than just the peaks. For example, in earlier studies on cognitive mobility between pairs of disciplines, it has been shown that the rate of migration is closely associated with affinity between fields, though it is not obvious from the prominent examples cited above [Wanger-Doebler].

 

We define an instance of migration by two papers belonging to two different fields written in succession by the same individual. More than 300,000 journal papers were scanned from Mathematical Reviews for 17 years (1959-75) and bi-directional pairwise data (A->B and B->A) collected for migrations between 39 subfields with more than 3000 papers each. Smaller areas that contributed less than 1% to the literature (total<10%) were dropped.  Only the first author of a paper has been considered in counting migrations. The unsymmetric directed matrix of migration counts was symmetrized for further analysis.  

 

The objective here is to understand relationships between the subfields of mathematics using direct embodied flows of knowledge in terms of migrations of individual researchers between them. Network maps on the structure of science generally employ other forms of knowledge flow, such as citations [Leydesdorff, Klavans, Boyack, Borner].  The paper also discusses similarities and differences in the two approaches.

 

 

Contractor, Noshir

nosh@northwestern.edu

   

From Disasters to WoW: Enabling Knowledge Networks in the 21^st century

Abstract: Recent advances in digital technologies invite consideration of organizing as a process that is accomplished by global, flexible, adaptive, and ad hoc networks that can be created, maintained, dissolved, and reconstituted with remarkable alacrity. A central challenge, spurred by these  developments,  is that the nature of teams and how they are assembled has changed radically. Using examples from his research in a wide range of activities such as disaster response, Communities of Practice at Procter & Gamble, public health and massively multiplayer online games (like World of Warcraft), Contractor will present a visual-analytic framework to Discover, Diagnose, and Design our 21st century knowledge networks.

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 Madhavan, Ravi 

Associate Professor of Business Administration

University of Pittsburgh

rmadhavan@katz.pitt.edu

 

Meta-analytic Syntheses of Network Studies: Promise and Pitfalls

 

Abstract:  Studies across many disciplines have focused on the performance impact of network structures within and across organizations, but empirical results have not always been convergent across studies. As an increasing number of empirical network studies are added to the literature, keeping pace with growing interest in networks, there is a need to develop ways to reliably synthesize findings from multiple studies. I will present an illustrative set of meta-analyses that indicates tenuous performance effects for network structure overall, with very weak Size and Centrality effects, and somewhat stronger Autonomy effects. Network effects appear to be stronger for interpersonal networks than for inter-organizational networks. Implications for continuing research into strategic networks include level of analysis issues and contingency effects. Building on this illustration, I will review the handful of available meta-analyses in the network literature to elicit the potential benefits of such an approach. Further, I will discuss the strengths and weaknesses of meta analytic techniques for the quantitative synthesis of network studies. As empirical evidence on networks accumulates, network scholars who seek to draw valid conclusions from a broad base of studies should evaluate meta-analytic synthesis as a potential aid.

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  Mehra, Ajay

Associate Professor, University of Kentucky

ajaymehra1@gmail.com

   

Self-Monitoring Personality and Network Churn: A Longitudinal Study of the Psychological Origins of Structural Brokerage

 

Co-authored with

Zuzana Sasovova, Vrije Universiteit Amsterdam

Michaéla C. Schippers , RSM Erasmus University Rotterdam

 

Abstract:Research has consistently shown that individuals who occupy brokerage positions (i.e., positions that connect otherwise unconnected others) in informal workplace networks tend to outperform their peers. But the question of why some people rather than others come to occupy brokerage positions has received relatively little attention. In this study, we build on a growing but controversial line of work that locates the origins of network brokerage in stable differences in self-monitoring personality. Drawing on two waves of data (nine months apart) from 170 members of a radiology department, located in the Netherlands, we found that high self-monitors, relative to low self-monitors, were more likely to occupy brokerage positions connecting otherwise unconnected others in their social network; and this effect persisted over time even as some of the initial brokerage positions disappeared and new ones appeared. We also found evidence for greater ―churn‖—i.e., the making and breaking of ties over time— in the social networks of high self-monitors than in the social networks of low self-monitors. That the relationship between self-monitoring personality and network brokerage was stable despite network churn suggests that the structure of social networks can be traced back to stable dispositional differences.

 

Reflections on a Digital Ecosystem Building for Indian Agriculture Extension Service in India and Social Network Analysis for Impact Evaluation

Pattanaik, Debashis

and 

 Jayanta Chatterjee

 

Abstract: Indian agriculture, that engages about six hundred million people across the vast expanse of the sub continent is a large socio-technical system that has earlier shown remarkable adaptive over five decades. This complex adaptive system however has lately started to languish and need infusion and diffusion of knowledge driven innovation across the entire value chain. Digital Ecosystem for Agriculture and Rural Livelihood (DEAL) is step toward knowledge driven agriculture in India. In this paper we try to explore how complex activities in a Digital Ecosystem (DE) become self-organizing and self-catalyzing through networks. We propose that that the process of creating a self propagating content/knowledge network and can be enhanced by efficient networking of many conversations of actors in a network. This can then create a digital ecosystem and a dynamic system sustained by many feedback loops. Key aspects of the ‘diffusion of innovation’ processes are the ‘dialectic interaction among the ‘innovation itself’, the ‘social system’ and the ‘communication channels’ through which the social system ‘members’ learn about the innovation and the ‘timing’ of the processes. Our observations suggest that a knowledge portal such as DEAL best facilitates the process of language reproduction in trust-relationship based framework. We argue that communication builds a different kind of network in a DE i.e., a network of practice (NoP) that creates many conversation loops through discursive interaction of different language communities.

 

 

Sinha, Sitabhra

The Emergence of Modular & Hierarchical Complex Networks in the Social Arena

 

Abstract: Complex networks, comprising tens to thousands of nodes are ubiquitous in society, ranging from acquaintance networks (of interest to sociologists) to stock interaction networks (in the context of financial markets). A large number of such systems exhibit common structural motifs which appear to be universal. Two examples are (i) modularity, where the network is divided into several connected clusters with the connection density in each cluster being significantly higher than that for the entire network, and (ii) hierarchy, where the connection structure can exhibit several levels of organization at different scales. Recent advances in re-building networks from empirical data have shown the ubiquity of such structures. Two examples of such reconstructed networks will be briefly reported in this talk: that for the stock interaction network in the Indian financial market and a macaque social network in the wild. We will then explore the reason
 behind the widespread emergence of such structures, and show that modularity and hierarchy can arise as a result of a complex system responding to multiple constraints on performance and resource. Also, the existence of hierarchical networks in social organizations can explain empirically established social distributions, e.g., the Pareto distribution of income. Finally, we will report some of our recent results on the dynamics of social games (e.g., Prisoners' Dilemma) in such modular networks, and speculate on how modularity could have arisen in social structures through co-evolution with trust in reciprocal cooperation.