Images as Data for Social Science Research
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
Andreu Casas, Vrije Universiteit, Amsterdam
John D. Wilkerson, University of Washington
August 2020
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9781108816854
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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.
Product details
August 2020Paperback
9781108816854
75 pages
225 × 151 × 5 mm
0.14kg
32 b/w illus.
Available
Table of Contents
- 1. Introduction
- 2. Prerequisites for computer vision methods and tutorials
- 3. Introduction to CNNs for social scientists
- 4. Overview of fine-tuning a CNN classifier for images
- 5. Political science working example: images related to a Black Lives Matter protest
- 6. The promise and limits of autotaggers
- 7. Application: fine-tuning an open source CNN
- 8. Legal and ethical concerns in using images as data
- 9. Conclusion
- 10. References.
