Danielly Sorato


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A Multilingual Dataset for Investigating Stereotypes and Negative Attitudes Towards Migrant Groups in Large Language Models
Danielly Sorato | Carme Colominas Ventura | Diana Zavala-Rojas
Proceedings of the 16th International Conference on Computational Processing of Portuguese


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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.

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The Multilingual Corpus of Survey Questionnaires Query Interface
Danielly Sorato | Diana Zavala-Rojas
Proceedings of the 5th Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature

The dawn of the digital age led to increasing demands for digital research resources, which shall be quickly processed and handled by computers. Due to the amount of data created by this digitization process, the design of tools that enable the analysis and management of data and metadata has become a relevant topic. In this context, the Multilingual Corpus of Survey Questionnaires (MCSQ) contributes to the creation and distribution of data for the Social Sciences and Humanities (SSH) following FAIR (Findable, Accessible, Interoperable and Reusable) principles, and provides functionalities for end-users that are not acquainted with programming through an easy-to-use interface. By simply applying the desired filters in the graphic interface, users can build linguistic resources for the survey research and translation areas, such as translation memories, thus facilitating data access and usage.