Student Scholar Symposium Abstracts and Posters

Document Type

Poster

Publication Date

Spring 5-1-2024

Faculty Advisor(s)

Dr. Laura Loustau

Abstract

Computational linguistics is an increasingly ubiquitous field, serving as the basis for artificial intelligence and machine translation. It aims to analyze the syntax and semantics of individual words and phrases. While there have been in-depth advancements in computational linguistics strategies for the English language, others have not been developed as thoroughly. This lack of emphasis on multilingualism has contributed to the disappearance of Hispanic perspectives in the digital world. Especially those of indigenous heritage, as the decline of many indigenous languages has been exacerbated by the lack of digital translation services. Sentiment analysis is a branch of computational linguistics that analyzes the sentiment of a word or phrase on a scale of positivity and negativity. As with computational linguistics as a whole, the majority of resources for analyzing sentiments of text are developed using the English language. There exist methodologies for performing analyses on multiple languages, such as parallel corpora for performing translations with English as well as the incorporation of multiple languages in one data set. Regardless of the method of implementation, it is proven that utilizing multiple languages in data can increase the accuracy of the resulting sentiment scores. A comparative analysis is performed on multiple data sets containing tweets in English and Spanish from the social media platform Twitter. These analyses result in sentiment scores for each group of data. The accuracy of each analysis is then compared, with the hypothesis that English tweets will provide a higher accuracy than Spanish tweets, given the robust resources for analyzing the sentiments of English texts. Finally, both English and Spanish tweets will be analyzed together, demonstrating the results of multilingual sentiment analysis.

Comments

Presented at the Spring 2024 Student Scholar Symposium at Chapman University.

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