Images as Data for Social Science Research: An Introduction to Convolutional Neural Nets for Image Classification...

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Nora Webb Williams (University of Illinois, Urbana-Champaign) Andreu Casas (Vrije Universiteit, Amsterdam)

Images as Data for Social Science Research

An Introduction to Convolutional Neural Nets for Image Classification

Nora Webb Williams (University of Illinois, Urbana-Champaign), Andreu Casas (Vrije Universiteit, Amsterdam), John D. Wilkerson (University of Washington)

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English

Cambridge University Press
13 August 2020

Research methods: general; Social research & statistics; Politics & government; Data capture & analysis; Data mining

Series: Elements in Quantitative and Computational Methods for the Social Sciences

Summary
Details

Images play a crucial role in shaping and reflecting political life. Digitization has vastly increased the presence of such images in daily life, creating valuable new research opportunities for social scientists. We show how recent innovations in computer vision methods can substantially lower the costs of using images as data. We introduce readers to the deep learning algorithms commonly used for object recognition, facial recognition, and visual sentiment analysis. We then provide guidance and specific instructions for scholars interested in using these methods in their own research.

By: Nora Webb Williams (University of Illinois Urbana-Champaign), Andreu Casas (Vrije Universiteit, Amsterdam), John D. Wilkerson (University of Washington)
Imprint: Cambridge University Press
Country of Publication: United Kingdom
Dimensions: Height: 225mm, Width: 151mm, Spine: 5mm
Weight: 140g
ISBN: 9781108816854
ISBN 10: 1108816851
Series: Elements in Quantitative and Computational Methods for the Social Sciences
Pages: 75
Publication Date: 13 August 2020
Audience: General/trade , ELT Advanced
Format: Paperback
Publisher's Status: Active