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Theories of Communication Networks by Noshir Contractor and Peter R. Monge (2003, Trade Paperback)

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Theories of Communication Networks presents solutions to all five problems. The authors develop a multitheoretical model that relates different social science theories with different network properties.

About this product

Product Identifiers

PublisherOxford University Press, Incorporated

ISBN-100195160371

ISBN-139780195160376

eBay Product ID (ePID)2360607

Product Key Features

Number of Pages432 Pages

Publication NameTheories of Communication Networks

LanguageEnglish

Publication Year2003

SubjectBusiness Communication / General, Communication Studies, General, Social Psychology

TypeTextbook

AuthorNoshir Contractor, Peter R. Monge

Subject AreaSocial Science, Language Arts & Disciplines, Business & Economics, Psychology

FormatTrade Paperback

Dimensions

Item Height0.6 in

Item Weight20.9 Oz

Item Length6 in

Item Width9.1 in

Additional Product Features

Intended AudienceScholarly & Professional

LCCN2002-011753

Dewey Edition21

IllustratedYes

Dewey Decimal302

Table Of Content1. Networks and Flows in Organizational CommunicationPart I: The Multitheoretical, Multilevel Framework2. Network Concepts, Measures, and the Multitheoretical, Multilevel Analytical Framework3. Communication and Knowledge Networks as Complex Systems4. Computational Modeling of NetworksPart II: Social Theories for Studying Communication Networks5. Theories of Self-Interest and Collective Action6. Contagion, Semantic, and Cognitive Theories7. Exchange and Dependency Theories8. Homophily, Proximity, and Social Support Theories9. Evolutionary and Coevolutionary TheoriesPart III: Integration10. MultiTheoretical, Multilevel Models of Communication and Other Organizational NetworksAppendix: Data Sets Used in Chapter 2ReferencesAuthor IndexSubject Index

SynopsisTo date, most network research contains one or more of five major problems. First, it tends to be atheoretical, ignoring the various social theories that contain network implications. Second, it explores single levels of analysis rather than the multiple levels out of which most networks are comprised. Third, network analysis has employed very little the insights from contemporary complex systems analysis and computer simulations. Foruth, it typically uses descriptive rather than inferential statistics, thus robbing it of the ability to make claims about the larger universe of networks. Finally, almost all the research is static and cross-sectional rather than dynamic. Theories of Communication Networks presents solutions to all five problems. The authors develop a multitheoretical model that relates different social science theories with different network properties. This model is multilevel, providing a network decomposition that applies the various social theories to all network levels: individuals, dyads, triples, groups, and the entire network. The book then establishes a model from the perspective of complex adaptive systems and demonstrates how to use Blanche, an agent-based network computer simulation environment, to generate and test network theories and hypotheses. It presents recent developments in network statistical anlysis, the p* family, which provides a basis for valid multilevel statistical inferences regarding networks. Finally, it shows how to relate communication networks to other networks, thus providing the basis in conjunction with computer simulations to study the emergence of dynamic organizational networks., Theories of Communication Networks presents solutions to all five problems. The authors develop a multi-theoretical model that relates different social science theories with different network properties. This model is multilevel, providing a network decomposition that applies the various social theories to all network levels: individuals, dyads, triples, groups, and the entire network. The book then establishes a model from the perspective of complex adaptive systems and demonstrates how to use Blanche, an agent-based network computer simulation environment, to generate and test network theories and hypotheses. It presents recent developments in network statistical analysis, the p* family, which provides a basis for valid multilevel statistical inferences regarding networks. Finally, it shows how to relate communication networks to other networks, thus providing the basis in conjunction with computer simulations to study the emergence of dynamic organizational networks., To date, most network research contains one or more of five major problems. First, it tends to be atheoretical, ignoring the various social theories that contain network implications. Second, it explores single levels of analysis rather than the multiple levels out of which most networks are comprised. Third, network analysis has employed very little the insights from contemporary complex systems analysis and computer simulations. Foruth, it typically uses descriptive rather than inferential statistics, thus robbing it of the ability to make claims about the larger universe of networks. Finally, almost all the research is static and cross-sectional rather than dynamic. Theories of Communication Networks presents solutions to all five problems. The authors develop a multitheoretical model that relates different social science theories with different network properties. This model is multilevel, providing a network decomposition that applies the various social theories to all network levels: individuals, dyads, triples, groups, and the entire network. The book then establishes a model from the perspective of complex adaptive systems and demonstrates how to use Blanche, an agent-based network computer simulation environment, to generate and test network theories and hypotheses. It presents recent developments in network statistical analysis, the p* family, which provides a basis for valid multilevel statistical inferences regarding networks. Finally, it shows how to relate communication networks to other networks, thus providing the basis in conjunction with computer simulations to study the emergence of dynamic organizational networks.

LC Classification NumberHM1111.M664 2002