Group Processes

Data-Driven Computational Approaches de

,

Éditeur :

Springer


Collection :

Computational Social Sciences

Paru le : 2017-03-07

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Description


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.

Pages
206 pages
Collection
Computational Social Sciences
Parution
2017-03-07
Marque
Springer
EAN papier
9783319489407
EAN PDF
9783319489414

Informations sur l'ebook
Nombre pages copiables
2
Nombre pages imprimables
20
Taille du fichier
7721 Ko
Prix
116,04 €
EAN EPUB
9783319489414

Informations sur l'ebook
Nombre pages copiables
2
Nombre pages imprimables
20
Taille du fichier
5366 Ko
Prix
116,04 €