Group Processes

Data-Driven Computational Approaches

Автор: Andrew Pilny, Marshall Scott Poole

Език:

Корици: С твърди корици

Издател: Springer International Publishing AG

Наличност: Външен склад

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This volume introduces a series of different data-driven computational methods for analyzing group p...

Информация за книгата

Автор

Andrew Pilny, Marshall Scott Poole

Език

Английски език

Корици

Книга - С твърди корици

Издадена

2017

страници

206

EAN

9783319489407

ISBN

3319489402

Enbook ID

15194733

Издател

Springer International Publishing AG

Теглоt

4439

Размери

155 x 235 x 14

Пълно описание

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 methods adapted 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.

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