Maria del Carme Colominas Ventura


Fixing paper assignments

  1. Please select all papers that belong to the same person.
  2. Indicate below which author they should be assigned to.
Provide a valid ORCID iD here. This will be used to match future papers to this author.
Provide the name of the school or the university where the author has received or will receive their highest degree (e.g., Ph.D. institution for researchers, or current affiliation for students). This will be used to form the new author page ID, if needed.

TODO: "submit" and "cancel" buttons here


2021

pdf bib
Using Word Embeddings to Quantify Ethnic Stereotypes in 12 years of Spanish News
Danielly Sorato | Diana Zavala-Rojas | Maria del Carme Colominas Ventura
Proceedings of the 19th Annual Workshop of the Australasian Language Technology Association

The current study provides a diachronic analysis of the stereotypical portrayals concerning seven of the most prominent foreign nationalities living in Spain in a Spanish news outlet. We use 12 years (2007-2018) of news articles to train word embedding models to quantify the association of such outgroups with drug use, prostitution, crimes, and poverty concepts. Then, we investigate the effects of sociopolitical variables on the computed bias series, such as the outgroup size in the host country and the rate of the population receiving unemployment benefits. Our findings indicate that the texts exhibit bias against foreign-born people, especially in the case of outgroups for which the country of origin has a lower Gross Domestic Product per capita (PPP) than Spain.