El índice de sentimiento en las redes sociales y su impacto en los rendimientos del S&P 500

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The Anáhuac Journal
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Publicado: Jun 26, 2024
DOI: https://doi.org/10.36105/theanahuacjour.2024v24n1.08
Palabras clave:
Twitter, redes sociales, procesamiento del lenguaje natural, análisis de sentimiento, inteligencia artificial, noticias

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Lizeth Gordillo Martínez
EGADE Business School, Tecnológico de Monterrey, México
https://orcid.org/0009-0000-9210-4955

Resumen

El estudio de la construcción y el análisis de índices de sentimiento en redes sociales es una técnica reciente que ha captado interés por su capacidad para identificar tendencias en los precios de las acciones. Además, la aplicación de inteligencia artificial para analizar rápidamente grandes volúmenes de datos de diversas fuentes de información ha creado una nueva forma de evaluar información masiva de redes sociales. El procesamiento del lenguaje natural (NLP, por sus siglas en inglés) es el método preferido que se sigue en la investigación. Originado en los años cincuenta, el NLP surgió de la intersección entre la inteligencia artificial y la lingüística. En un comienzo se empleó para recuperar información textual, con métodos basados en estadísticas para indexar y buscar de manera eficaz en grandes secciones de texto.

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Gordillo Martínez, L. (2024). El índice de sentimiento en las redes sociales y su impacto en los rendimientos del S&P 500. The Anáhuac Journal, 24(1), Págs. 222–245. https://doi.org/10.36105/theanahuacjour.2024v24n1.08
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Vol. 24 Núm. 1 (2024): The Anáhuac Journal, Vol. 24, núm. 1, 2024, Primer Semestre
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Biografía del autor/a

Lizeth Gordillo Martínez, EGADE Business School, Tecnológico de Monterrey, México

Lizeth Gordillo Martínez began her professional career as coordinator for the Center for Technology and Financial Innovation while a BA student in international trade at the Tecnológico de Monterrey, Mexico City Campus. Gordillo Martínez conducted training workshops on databases specializing in finance and technology in various companies such as Bloomberg, Reuters, Economática, SaS, Eviews, and Numerix, and taught financial administration to 14 generations of students at the undergraduate level. Starting in 2008, she worked full-time leading negotiations with clients from the financial sector in the Latin America region at multinational companies with a technological and financial profile like Bloomberg, Thomson Reuters, Numerix, and Identy. Among her professional achievements are the creation of financial labs for private universities with Bloomberg and Reuters terminals, and the implementation of a Thomson Reuters ticker with financial indicators at the Mexican Stock Exchange (BMV) building. Gordillo Martínez secured Grupo Bancolombia as the first client—and first international bank—for Numerix in Latin America. There, she implemented a CVA calculation module for the bank’s treasury. At the same time, she continued with her graduate studies, earning a master’s degree in Finance, and in 2021 she started a PhD in financial sciences.

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