On July 24, Science published a special issue on complex systems and networks.

Science - Complexity cover

The issue description from Science:

In the 24 July 2009 issue, Science highlights how network analysis is allowing us to understand how the world works from new vantage points. Perspective articles examine the foundations of network analysis and its applications across disciplinary fields from economics to ecology; News stories look at the use of network tools to study social phenomena; and a Review article explains how molecular biologists are using networks to analyze basic cellular circuitry. Science Careers highlights careers in network science and the 28 July issue of Science Signaling delves into the dynamics of cell signaling networks.

Even online, the neocortex is the limit

THAT Facebook, Twitter and other online social networks will increase the size of human social groups is an obvious hypothesis, given that they reduce a lot of the friction and cost involved in keeping in touch with other people. Once you join and gather your “friends” online, you can share in their lives as recorded by photographs, “status updates” and other titbits, and, with your permission, they can share in yours. Additional friends are free, so why not say the more the merrier?”

Read more in The Economist.

Imputation of missing network data: Some simple procedures

Huisman, M. (2009), Journal of Social Structure, 10(1).

Analysis of social network data is often hampered by non-response and missing data. Recent studies show the negative effects of missing actors and ties on the structural properties of social networks. This means that the results of social network analyses can be severely biased if missing ties were ignored and only complete cases were analyzed. To overcome the problems created by missing data, several treatment methods are proposed in the literature: model-based methods within the framework of exponential random graph models, and imputation methods. In this paper we focus on the latter group of methods, and investigate the use of some simple imputation procedures to handle missing network data. The results of a simulation study show that ignoring the missing data can have large negative effects on structural properties of the network. Missing data treatment based on simple imputation procedures, however, does also have large negative effects and simple imputations can only successfully correct for non-response in a few specific situations.

Networks of contextualized data: a framework for cyberinfrastructure data management

Pamela E. Carter, Gina Green(2009), Communications of the Association for Computing Machinery. Pages 105-109.

The Prospects for Cyberocracy (Revisited)

David Ronfeldt and Danielle Varda (2009), Social Science Research Network.

The deepening of the information age will alter the nature of the state so thoroughly that something new emerges: cyberocracy. While it is too early to say precisely what a cyberocracy will look like, the outcomes will include new kinds of democratic, totalitarian, and hybrid governments, along with new kinds of state-society relations. Thus, optimism about the information revolution should be tempered by an anticipation of its potential dark side. This paper reiterates the view of the cyberocracy concept as first stated in 1992, and then offers a postscript for 2008. It speculates that information-age societies will develop new sensory apparatuses, a network-based social sector, new modes of networked governance, and ultimately the cybercratic nexus-state as a successor to the nation-state.

Intraorganizational Networks, Interorganizational Networks, and the Impact of Central Inventors: A Longitudinal Study of Pharmaceutical Firms.

Srikanth Paruchuri (2009)Organization science, Published online before print January 22, 2009.

This paper proposes that a mechanism through which a firm’s location in the interorganizational network influences the firm’s internal innovation activities is modifying the amount of information flowing within the firm. Exploring a firm’s internal innovation activities, I hypothesized that structural centrality of an inventor in the intrafirm co-inventing network is associated with her impact on her firm’s innovation activities in an inverted-U-shape relation. I further hypothesized that this relationship is moderated by the firm’s centrality and span of structural holes in the interfirm network. I found strong support for these hypotheses in a longitudinal study of eight large pharmaceutical firms. The findings in this paper, apart from having managerial implications, have implications for research on alliances, network studies, and innovation processes.

Firm Scope Experience, Historic Multimarket Contact with Partners, Centrality, and the Relationship Between Structural Holes and Performance.

Andrew V. Shipilov (2009), Organization Science, January-February 2009; 20: 85 – 106.

This study investigates characteristics that affect the relationship between firms’ positions in a network of collaborative ties with other firms and their performance. Firms located in similarly structured networks rich in structural holes may obtain different performance results depending on their (1) capacity to absorb heterogeneous information, (2) ability to protect against partner noncooperation, and (3) bargaining power. Read the rest of this entry »