Posts

Role of Internet-based Information Flows and Technologies in Electoral Revolutions: Ukraine’s Orange Revolution

Volodymyr V. Lysenko and I have co-authored a paper that examines the role played by Internet-based information flows and technologies in electoral revolutions. Recent events have drawn attention to the use of Internet-based information and communication technologies (ICTs) in the political process. For instance, ICTs played an important role during attempts at electoral revolutions in Moldova in April 2009 and Iran in June 2009. Employing a case study approach, we examine the part played by ICTs during the Orange Revolution in Ukraine (2000-2004). Roles and activities of the dissenters, as well as their associates, the incumbent authorities and their allies are analyzed with regard to Internet-based technologies during the electoral revolution in Ukraine. The case of the Orange Revolution is particularly salient, as even though only 1-2 percent of the Ukrainian population had access to the Internet, this was sufficient to mobilize the citizens towards an eventually successful revolution. This paper lays the groundwork for further investigations into use of ICTs by political dissenters. The paper will appear in a forthcoming issue of First Monday.

Measuring Agility of Networked Organizational structures via Network Entropy and Mutual Information

Yuan Lin, Sumit Roy, and I have authored a paper that examines the use of network entropy and mutual information to measure the agility of networked organizational structures. The paper will appear in Applied Mathematics and Computation.

Abstract
While the agility of networked organizational structures is important for organizational performance, studies on how to evaluate it remain scant, probably because the difficulty in measuring network evolution. In this conceptual paper, we propose two measures – network entropy and mutual information – to characterize the agility of networked organizational structure. Rooted in graph theory and information theory, these two measures capture network evolution in a comprehensive and parsimonious way. They indicate the uncertainty (or disorder) at the network level as well as the degree distribution at the individual level. We also propose an algorithm for applying them in the scenario of adding links to a network while holding the number of nodes fixed. Both simulated and real networks are used for demonstration. Implications and areas for future research are discussed in the end.

Lin, Y., Desouza, K.C., and Roy, S. “Measuring Agility of Networked Organizational structures via Network Entropy and Mutual Information,” Applied Mathematics and Computation, Forthcoming.