9780521365680-0521365686-Algebraic Models for Social Networks (Structural Analysis in the Social Sciences, Series Number 7)

Algebraic Models for Social Networks (Structural Analysis in the Social Sciences, Series Number 7)

ISBN-13: 9780521365680
ISBN-10: 0521365686
Edition: 0
Author: Philippa Pattison
Publication date: 1993
Publisher: Cambridge University Press
Format: Hardcover 336 pages
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Book details

ISBN-13: 9780521365680
ISBN-10: 0521365686
Edition: 0
Author: Philippa Pattison
Publication date: 1993
Publisher: Cambridge University Press
Format: Hardcover 336 pages

Summary

Algebraic Models for Social Networks (Structural Analysis in the Social Sciences, Series Number 7) (ISBN-13: 9780521365680 and ISBN-10: 0521365686), written by authors Philippa Pattison, was published by Cambridge University Press in 1993. With an overall rating of 4.5 stars, it's a notable title among other Personality (Psychology & Counseling) books. You can easily purchase or rent Algebraic Models for Social Networks (Structural Analysis in the Social Sciences, Series Number 7) (Hardcover) from BooksRun, along with many other new and used Personality books and textbooks. And, if you're looking to sell your copy, our current buyback offer is $0.3.

Description

As the analysis of social networks, or networks of interpersonal and social relationships among social groups, has become an increasingly important method of research in several of the social and behavioral sciences, the gathering of network data has outpaced the development of new methods for its analysis. Addressing the need for new analytical tools, Philippa Pattison presents a number of new algebraic models for the analysis of network data, explaining in the process the rationale for an algebraic approach. Models are developed for both complete networks, meaning those representing the social ties between all pairs of members in a given group, and local networks, meaning those structured around the social ties of one particular group member. Many applications are presented and the ways that these methods can address a number of important issues confronting network analysis are explained.

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