Group Processes

Data-Driven Computational Approaches

  • Andrew Pilny
  • Marshall Scott Poole

Part of the Computational Social Sciences book series (CSS)

Table of contents

  1. Front Matter
    Pages i-v
  2. Andrew Pilny, Marshall Scott Poole
    Pages 1-4
  3. Andrew Pilny, Amanda R. Slone
    Pages 5-27
  4. Iftekhar Ahmed, Jeffrey Proulx, Andrew Pilny
    Pages 29-49
  5. Carter T. Butts, Christopher Steven Marcum
    Pages 51-92
  6. Natalie J. Lambert
    Pages 93-117
  7. Toshio Murase, Marshall Scott Poole, Raquel Asencio, Joseph McDonald
    Pages 119-144
  8. Ankit Sharma, Jaideep Srivastava
    Pages 145-180

About this book


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.


analyzing group processes computational analytics machine learning modeling relational events social sequence analysis team assembly algorithm

Editors and affiliations

  • Andrew Pilny
    • 1
  • Marshall Scott Poole
    • 2
  1. 1.University of KentuckyLexingtonUSA
  2. 2.University of IllinoisUrbanaUSA

Bibliographic information