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Group Processes

Group Processes

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Part of the Computational Social Sciences series

Hardback
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Group Processes Synopsis

This volume introduces a series of different data-driven computational methods for analyzing group processes through didactic and tutorial-based examples. Group processes are of central importance to many sectors of society, including government, the military, health care, and corporations. Computational methods are better suited to handle (potentially huge) group process data than traditional methodologies because of their more flexible assumptions and capability to handle real-time trace data.

Indeed, the use of methods under the name of computational social science have exploded over the years. However, attention has been focused on original research rather than pedagogy, leaving those interested in obtaining computational skills lacking a much needed resource. Although the methods here can be applied to wider areas of social science, they are specifically tailored to group process research.

A number of data-driven methodsadapted to group process research are demonstrated in this current volume. These include text mining, relational event modeling, social simulation, machine learning, social sequence analysis, and response surface analysis. In order to take advantage of these new opportunities, this book provides clear examples (e.g., providing code) of group processes in various contexts, setting guidelines and best practices for future work to build upon.

This volume will be of great benefit to those willing to learn computational methods. These include academics like graduate students and faculty, multidisciplinary professionals and researchers working on organization and management science, and consultants for various types of organizations and groups.

About This Edition

ISBN: 9783319489407
Publication date:
Author: Andrew Pilny, Marshall Scott Poole
Publisher: Springer an imprint of Springer International Publishing
Format: Hardback
Pagination: 206 pages
Series: Computational Social Sciences
Genres: Computer modelling and simulation
Expert systems / knowledge-based systems
Knowledge management
Sociology
Occupational and industrial psychology
Data mining
Databases

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