Network theory

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

A New Measurement for the Importance of Nodes in Networks

Abstract: Networks are widely used in a variety of different fields and attract more and more researchers. Centrality analyses, one of the research hotspots, provide answers with measures that define the importance of nodes. However, classical centrality analyses usually have high expensive complexity. Moreover, we propose a new measurement for the importance of nodes in networks to avoid some shortcomings of classical measurements. DC centrality integrates two different measurements-degree measurement and cohesion centrality. We also argue the limitation of relying on single measurement. The experiment results show that DC centrality can get better performance.

Measuring Cohesion of Software Systems Using Weighted Directed Complex Networks

Abstract: Network theory has been demonstrated as an effective approach for better understanding and analysis of software systems from a systematic perspective. In this paper, we develop a directed and weighted software dependency network model to analyse software systems from a complex network perspective. In particular, to measure the "High Cohesion and Low Coupling" nature of object-oriented software systems, we propose to use a directed and weighted modularity index, which can better reflect the cohesion of software systems. Experiments are conducted on a series of open source object-oriented software systems with various scales, and the results show that the directed and weighted modularity can better characterize software systems with different cohesion.

The Relationship between Informal Knowledge Sharing Network and Individual Learning in Organizations: Does the Structuring of Activities Matter?

Abstract: Capitalizing on organizational network theory, we address the relationship between informal-knowledge-sharing-network characteristics (in-degree and out-degree centrality) and the level of internal and external learning. Specifically, the paper examines differences in the use of various relationships when employees are learning internally or externally and explores the moderating role of the perceived organic structuring of activities. The results show the employees resort to informal-knowledge-generating relationships (informal in-degree) to obtain knowledge internally, whereas, when learning externally, employees rely on informal- -knowledge-sharing relationships (informal out-degree) to disseminate the knowledge they obtain from outside the organization. The anticipated moderating role of the organic structuring of activities is not confirmed, holding important implications for both theory and practice.

A Minimal Agent-Based Model Reproduces the Overall Topology of Interbank Networks

Abstract: The description of the empirical structure of interbank networks constitutes an important field of study since network theory can be used as a powerful tool to assess the resilience of financial systems and their robustness against failures. On the other hand, the development of reliable models of interbank market structure is relevant as they can be used to analyze systemic risk in the absence of transaction data or to test statistical hypotheses regarding network properties. Based on a detailed data-driven analysis of bank positions (assets and liabilities) taken from the Bankscope database, we here develop a minimal, stochastic, agent-based network model that accounts for the basic topology of interbank networks reported in the literature. The main assumption of our model is that loans between banks attempt to compensate assets and liabilities at each time step, and the model renders networks comparable with those observed in empirical studies. In particular, our model is able to qualitatively reproduce degree distributions, the distribution of the number of transactions, the distribution of exposures, the correlations with nearest-neighbor out-degree, and the clustering coefficient. As our simple model captures the overall structure of empirical networks, it can thus be used as a null model for testing hypotheses relative to other specific properties of interbank networks.

Innovation and market dynamics: A two-mode network approach to user-producer relation

Abstract: In this paper we propose a new mental representation of how markets, technology and their interaction concur in explaining the why of a certain innovation instead of another. We empirically test this theory in the telecommunication switches industry. We consider innovation as a new alignment of needs and opportunities, where markets and technology are not the sources, but the actors in this alignment process. In order to accomplish this task, we suggest proxies for technological opportunities, market needs, and, at the same time, for interactions of these two elements. We make use of a statistical tool that grasps the matching nature of this interactive phenomenon.