Network theory

About: Network theory is a research topic. Over the lifetime, 2257 publications have been published within this topic receiving 109864 citations.

Networks in Manuel Castells’ theory of the network society

Abstract: This paper discusses the conceptualization of network in Manuel Castells’ theory of network society. Castells’ early academic works were built on the structural analysis of capitalism and social movements in response to the contradictions of capitalist society, without any explicit connection to network analysis. Networks gradually appeared in Castells’ works in the late 1980s, when he became interested in the configuration of the relationships between technology, economy, and society. The culmination of this phase was his opus magnum, The Information Age trilogy, which introduced network as a key concept of his macro theory, even though he remained laconic about the concept itself. This is paradoxical, for Castells became possibly the most prominent figure globally in adopting network terminology in macro sociological theory, but at the same time made hardly any empirical, theoretical or methodological contribution to social network analysis or network theory in general. This implies that ‘network’ in Castells’ social theory is not an analytical concept but rather a powerful metaphor that served to capture his idea of the new social morphology of late capitalism.

Key Author Analysis in Research Professionals' Collaboration Network based on MST using Centrality Measures

Abstract: The importance of an actor in the network is measured by the different type of centrality metrics of Social Network Analysis (SNA). In the research community, who are the most prominent author or key on the network is the major discussion or research issue. Different types of centrality measures and citation based indices are available, but their result is varied from network to network. In this paper, we form a network of author and its co-author based on Maximum Spanning Tree and find out the key author based on social network analysis metrics like degree centrality, closeness centrality, betweenness centrality and eigenvector centrality. After that we compare the result of all centrality measures of MST based network and original network, betweenness centrality value increases and the other centrality value decreases. Finally, we conclude that the betweenness centrality is useful to analyze key author in this type of network.

A Comparison of Approaches to Computing Betweenness Centrality for Large Graphs

Abstract: Many algorithms require doing a large number of betweenness centrality calculations quickly, and accommodating this need is an active open research area. Two of the most important ways of addressing this problem are with approximated and distributed algorithms. It is difficult to know which approach will work best in practical situations, because results presented are often compared to similar algorithms, and universally recognized benchmarks do not exist. This paper evaluates one approximation approach and one distributed approach by applying each to the problem of node-based resilience measure clustering. This form of clustering is a good test for the algorithms, because it requires massive numbers of betweenness centrality calculations, as well as results that are accurate enough for the clustering to succeed. We find that with both the approximated and distributed approaches there is a trade-off between speed and accuracy, but each succeeds in reducing computation time by at least an order of magnitude.