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Computational Methods for Communication Science

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ACA
big data analysis
Category=GTC
Clustering Coefficient
Coder Training
Dashed Trend Line
Data Sets
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
General Public Users
Institutional Users
Latent Dirichlet Allocation
LDA Algorithm
LDA Topic
LDA Topic Modeling
machine learning in social science
network analysis techniques
Occupy Wall Street
Parliamentary Party Group Leaders
RF Classifier
Scientific Ecosystems
Scientific Teams
Sentiment Analysis
sentiment analysis tools
Sentiment Scores
supervised learning for Twitter research
Supervised Machine Learning
Team Assembly
text mining methods
Topic Modeling
topic modeling applications
Triadic Closure
Van Atteveldt
Web Archives
Word Embeddings

Product details

  • ISBN 9780367536169
  • Weight: 480g
  • Dimensions: 178 x 254mm
  • Publication Date: 30 Mar 2021
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: GB
  • Product Form: Hardback
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Description

Computational Methods for Communication Science showcases the use of innovative computational methods in the study of communication.

This book discusses the validity of using big data in communication science and showcases a number of new methods and applications in the fields of text and network analysis. Computational methods have the potential to greatly enhance the scientific study of communication because they allow us to move towards collaborative large-N studies of actual behavior in its social context. This requires us to develop new skills and infrastructure and meet the challenges of open, valid, reliable, and ethical "big data" research. This volume brings together a number of leading scholars in this emerging field, contributing to the increasing development and adaptation of computational methods in communication science.

The chapters in this book were originally published as a special issue of the journal Communication Methods and Measures.
About

Wouter van Atteveldt is Associate Professor of Political Communication at VU Amsterdam, the Netherlands. His research interests include computational communication science and the role of news and journalism in the functioning of democracy. He co-founded the ICA division on Computational Methods and is Editor-in-Chief of the journal Computational Communication Research.

Tai-Quan Peng is Associate Professor at the Department of Communication, Michigan State University, East Lansing, USA. His research interest lies in the application of computational methods to examine structure and dynamics of human communication phenomena on social and mobile media. He was the Inaugural Chair of the Computational Methods division at the International Communication Association.