Network theory

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

Proposal of Chance Index in Co-occurrence Network

Abstract: This paper proposes chance index that estimates whether a node is chance in a co-occurrence network. Recently, chance discovery researches are attractive for several domains. By using chance discovery, we can develop new business or predict earthquake. However, there is a problem that chance discovery requires analysts' inference from visualized network so that success and failure of chance discovery depend on analysists. In order to solve this problem, we analyzed the features from previous chance discovery researches and build the two hypotheses: 1 chance nodes have high betweenness centrality and 2 chance nodes connect to others with weak links. Based on the hypotheses, chance index is formulated by two terms about betweenness centrality and the strength of links. We confirm the usability of chance index from verification experiments, using Bush network, questionnaire network, interview network, and editorial network.

Scale-free Networks in Dictionaries

Abstract: The aim of this paper is to show, through the application of the mathematical model of scale-free networks, how the scale-free network of language is represented in the information contained in dictionaries. Research conducted in the last few decades has proven that every phenomenon of nature and society-the relations of so many various systems-is organised into a complex system of networks. Research has also proven that complex networks can be analysed with the help of a common network model, and that the application of this network theory allows us to discover features of the analysed system that are not observable by other methods. After the discovery of the significance of networks, broad experimental and theoretical studies were launched to reveal the nature of networks and to apply the findings, and research on scale-free networks is the most outstanding among these. If we accept that the three components of the terminological unit may be modelled with the scale-free terminological network model (Foris 2007), and that the language network is made up of at least these three networks, then we may suppose that dictionaries select and present various parts of this complex network from different approaches. The lexicographers. task-to put it simply-is to collect, record and make the data necessary for language use easily accessible. In order to meet this aim, dictionaries need to follow the three-sided structure of language networks. The various types of dictionaries compiled for different purposes developed a practical structure that reflects the structure of the language network. In the paper, I briefly touch upon the main characteristics of the scale-free network model that can be widely applied in linguistic research, and point out the lexicographic aspects of the model. Based on the network model we can draw conclusions concerning the practical structure of dictionaries. I demonstrate that the complex scale-free network structure of language containing three sub-systems enables us to use the language quickly and completely. I also illustrate and support the features of the language network model and its application with figures.

Network Theory and Analysis

Abstract: This article reviews developments in network analysis and its applications to problems of organization. From an arcane social science tradition focused chiefly on methods, it has evolved into a major paradigm for thinking about and researching relationships and social structure within and among organizations. Network ideas and methods have been embraced by organizational theorists in part because the world of organizations has itself changed: from centrally coordinated hierarchies to loosely linked strategic alliances and “network forms.” Methods issues continue to be important in network analysis; however, the data and the statistical methods appropriate to network study are quite different from those of other social and behavioral science domains. Network methods and models at varying levels of analysis are reviewed – node, dyad, subnetwork (clique or cluster), and network – and how they have been applied to recent subfields of organizational study. Keywords: network theory and analysis; data collection; levels and methods

Evolution of Networks - From Biological Nets to the Internet and WWW

Abstract: Networks have been recently recognized as playing a central role in understanding a wide range of systems spanning diverse scientific domains such as physics and biology, economics, computer science and information technology Specific examples run from the structure of the Internet and the World Wide Web to the interconnections of finance agents and ecological food webs These networked systems are generally made by many components whose microscopic interactions give rise to global structures characterized by emergent collective behaviour and complex topological properties In this context the statistical physics approach finds a natural application since it attempts to explain the various large-scale statistical properties of networks in terms of local interactions governing the dynamical evolution of the constituent elements of the system It is not by chance then that many of the seminal papers in the field have been published in the physics literature, and have nevertheless made a considerable impact on other disciplines Indeed, a truly interdisciplinary approach is required in order to understand each specific system of interest, leading to a very interesting cross-fertilization between different scientific areas defining the emergence of a new research field sometimes called network science The book of Dorogovtsev and Mendes is the first comprehensive monograph on this new scientific field It provides a thorough presentation of the forefront research activities in the area of complex networks, with an extensive sampling of the disciplines involved and the kinds of problems that form the subject of inquiry The book starts with a short introduction to graphs and network theory that introduces the tools and mathematical background needed for the rest of the book The following part is devoted to an extensive presentation of the empirical analysis of real-world networks While for obvious reasons of space the authors cannot analyse in every detail all the various examples, they provide the reader with a general vista that makes clear the relevance of network science to a wide range of natural and man-made systems Two chapters are then committed to the detailed exposition of the statistical physics approach to equilibrium and non-equilibrium networks The authors are two leading players in the area of network theory and offer a very careful and complete presentation of the statistical physics theory of evolving networks Finally, in the last two chapters, the authors focus on various consequences of network topology for dynamical and physical phenomena occurring in these kinds of structures The book is completed by a very extensive bibliography and some useful appendices containing some technical points arising in the mathematical discussion and data analysis The book's mathematical level is fairly advanced and allows a coherent and unified framework for the study of networked structure The book is targeted at mathematicians, physicists and social scientists alike It will be appreciated by everybody working in the network area, and especially by any researcher or student entering the field that would like to have a reference text on the latest developments in network science

Terminology and the theory of scale-free networks

Abstract: Summary The goal of these studies is to draw attention to the application of the theory of scale-free networks in terminology. In the last few years there have been a lot of publications on the application of the scale-free network model (for a summary see Barabasi 2002 and Csermely 2006). A brief summary of the basic information regarding networks will be provided and previous findings of linguistic research that were interpreted with the help of network models (terminology, quantitative linguistics, generative linguistics, psycholinguistics) will be surveyed. Before networks were widely researched, there were a great number of linguistic findings on natural languages that now lend themselves to new interpretation through network theory. In the paper calculations on the numeric data obtained from previous publications on quantitative linguistic research will be demonstrated. Finally, I will elaborate on some aspects of the application of network theory in terminology, and introduce the model of terminolo...