Images as data for social science research : an introduction to convolutional neural nets for image classification

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Full Title:: Images as data for social science research : an introduction to convolutional neural nets for image classification / Nora Webb Williams, Andreu Casas, John D. Wilkerson
Series Titles:: Elements in quantitative and computational methods for the social sciences,
Elements in quantitative and computational methods for the social sciences.

Additional Author/Creators:: Casas, Andreu, author
Wilkerson, John D., author

Summary:: 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.
Language:: English
Physical Type/Description:: 1 online resource : digital, PDF file(s).
General Note:: Title from publisher's bibliographic system (viewed on 17 Jul 2020).
Local Note:: Available to current Emory faculty, students and staff.