Quantifying Refugee and Migrant Portrayals in Literature and Media

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Abstract/Contents

Abstract: For his capstone project, Andrew Quirk developed a statistical analysis that examined depictions of refugees in media using NLP & NLU techniques, taking advantage of large datasets of multinational news (scraped using the Python Newspaper3k library) to understand differences in geographic depictions of refugees (Syrian refugee crisis, “African” refugee crisis, etc.). Utilizing existent human rights literature, news sources, and similar data models, Andrew found that language had a huge influence on how refugees were portrayed in various mediums, often being associated with danger and criminality, but also a sense of opportunity. Andrew hopes his project helps uncover nuances in the portrayal of people groups and validate the technique of word embeddings to reveal the unconscious biases that are embedded in news and literature.

Type of resource	text
Date created	[ca. June 2019]

Author	Quirk, Andrew

DOI	https://doi.org/10.25740/gy093vv6464
Location	https://purl.stanford.edu/gy093vv6464

Use and reproduction: User agrees that, where applicable, content will not be used to identify or to otherwise infringe the privacy or confidentiality rights of individuals. Content distributed via the Stanford Digital Repository may be subject to additional license and use restrictions applied by the depositor.
License: This work is licensed under a Creative Commons Attribution 4.0 International license (CC BY).

Preferred citation: Quirk, A. (2022). Quantifying Refugee and Migrant Portrayals in Literature and Media. Stanford Digital Repository. Available at https://purl.stanford.edu/gy093vv6464

Stanford Center for Human Rights and International Justice, Minor in Human Rights Capstone Projects

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