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Word embedding analysis on colonial history, present issues, and optimism toward the future in Senegal

Author

Listed:
  • Kamwoo Lee

    (University of Virginia)

  • Jeanine Braithwaite

    (University of Virginia)

  • Michel Atchikpa

    (Université Cheikh Anta Diop de Dakar)

Abstract

Language is a reflection of issues and value systems of a society. This study tries to understand sensitive public issues in Senegal through language use. To this end, we utilize word embeddings, a numerical word representation, to analyze concepts, connotations, and nuances of several words. State-of-the-art machine learning methods can effectively extract the word embeddings from a collection of texts. Since people in different societies possess different mindsets and language uses, comparing semantic differences of words in different corpora is an efficient way to draw cross-cultural insights and implications. In this study, we extract word embeddings from Senegalese newspapers and Wikipedia pages in French and then compare the results to identify different word sentiments in Senegalese cultures to understand the past, present, and future of the country.

Suggested Citation

  • Kamwoo Lee & Jeanine Braithwaite & Michel Atchikpa, 2021. "Word embedding analysis on colonial history, present issues, and optimism toward the future in Senegal," Computational and Mathematical Organization Theory, Springer, vol. 27(3), pages 343-356, September.
    • Handle: RePEc:spr:comaot:v:27:y:2021:i:3:d:10.1007_s10588-021-09335-y
    DOI: 10.1007/s10588-021-09335-y
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    References listed on IDEAS

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    1. Graham, Carol, 2012. "Happiness Around the World: The paradox of happy peasants and miserable millionaires," OUP Catalogue, Oxford University Press, number 9780199606283.
    2. Mamadou Diouf, 1998. "The French Colonial Policy of Assimilation and the Civility of the Originaires of the Four Communes (Senegal): A Nineteenth Century Globalization Project," Development and Change, International Institute of Social Studies, vol. 29(4), pages 671-696, October.
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