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A framework for the unsupervised and semi-supervised analysis of visual frames
This article introduces to political science a framework to analyze the content of political visual material through unsupervised and semi-supervised methods. It details the implementation of a tool from the computer vision field, the Bag of Visual Words, for the definition and extraction of ``tokens’‘ that allow researchers to build an Image-Visual Word matrix which emulates the Document-Term matrix in text analysis. This reduction technique is the basis for several tools familiar to social scientists, such as topic models, that permit exploratory, and semi-supervised analysis of images. The framework has gains in transparency, interpretability, and inclusion of domain knowledge with respect to other deep learning techniques. I illustrate the scope of the BoVW by conducting a novel visual structural topic model which focuses substantively on the identification of visual frames from the pictures of the migrant caravan from Central America.
Date:
5 June 2023, 14:00
Venue:
Manor Road Building, Manor Road OX1 3UQ
Venue Details:
Seminar Room A
Speaker:
Michelle Torres (Rice)
Organising department:
Department of Politics and International Relations (DPIR)
Organiser:
Spyros Kosmidis (University of Oxford)
Booking required?:
Not required
Audience:
Members of the University only
Editors:
Helen Morley,
Rebecca Freeman,
Daniel Burton
