Group Processes Data-Driven Computational Approaches
tarafından
Pilny, Andrew. editor.
Başlık
:
Group Processes Data-Driven Computational Approaches
Yazar
:
Pilny, Andrew. editor.
ISBN
:
9783319489414
Edisyon
:
1st ed. 2017.
Fiziksel Niteleme
:
VI, 206 p. 80 illus., 59 illus. in color. online resource.
Seri
:
Computational Social Sciences,
İçindekiler
:
Introduction -- Response Surface Models to Analyze Nonlinear Group Phenomena -- Causal Inference using Bayesian Network -- A Relational Event Approach to Modeling Behavioral Dynamics -- Text Mining Tutorial -- Sequential Synchronization Analysis -- Group Analysis using Machine Learning Techniques -- Simulation and Virtual Experimentation: Grounding with Empirical Data.
Özet
:
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.
Konu Başlığı
:
Computer simulation.
Social sciences -- Methodology.
Big data.
Data mining.
Applied psychology.
Knowledge management.
Simulation and Modeling. http://scigraph.springernature.com/things/product-market-codes/I19000
Methodology of the Social Sciences. http://scigraph.springernature.com/things/product-market-codes/X17000
Big Data/Analytics. http://scigraph.springernature.com/things/product-market-codes/522070
Data Mining and Knowledge Discovery. http://scigraph.springernature.com/things/product-market-codes/I18030
Industrial and Organizational Psychology. http://scigraph.springernature.com/things/product-market-codes/Y20030
Knowledge Management. http://scigraph.springernature.com/things/product-market-codes/515030
Yazar Ek Girişi
:
Pilny, Andrew.
Poole, Marshall Scott.
Ek Kurum Yazar
:
SpringerLink (Online service)
Elektronik Erişim
:
Materyal Türü | Barkod | Yer Numarası | Durumu/İade Tarihi |
---|
Electronic Book | 225743-1001 | QA76.9 .C65 | Springer E-Book Collection |