Prioritizing the Net Sentiment Score: A Banking Industry Case Study

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The Anáhuac Journal
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Published: Jun 26, 2024
DOI: https://doi.org/10.36105/theanahuacjour.2024v24n1.10
Keywords:
stock performance, net sentiment score (NSS), robust linear model regression, brand, value impact

Main Article Content

José Guadalupe Mendoza Macías
Quantum Analytics, Sinaloa, Mexico
Román Alejandro Mendoza Urdiales
Quantum Analytics, Sinaloa, Mexico
https://orcid.org/0000-0003-2888-156X

Abstract

This study analyzes the impact of social media comments on the stock performance of banks registered on the United States stock market. We use artificial intelligence to monitor and extract comments in real time, together with natural language processing, to identify the sentiment of each comment. Comments were classified as positive or negative and were added by the hour for each bank during the observed period. Our results showed that both positive and negative comments have a significant effect on the stock performance, with negative comments having a more pronounced, asymmetrical impact. This study contributes to understanding how social media interactions influence the market value of companies, highlighting the importance of monitoring and managing the online perception of the companies listed on the stock market.

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How to Cite
Mendoza Macías, J. G., & Mendoza Urdiales, R. A. (2024). Prioritizing the Net Sentiment Score: A Banking Industry Case Study. The Anáhuac Journal, 24(1), Págs. 272–293. https://doi.org/10.36105/theanahuacjour.2024v24n1.10
Issue
Vol. 24 No. 1 (2024): The Anáhuac Journal, Vol. 24, num. 1, 2024, First Semester
Section
Artículos
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This work is licensed under a Creative Commons Atribución-NoComercial-CompartirIgual 4.0 Internacional.

 

Author Biographies

José Guadalupe Mendoza Macías, Quantum Analytics, Sinaloa, Mexico

José Mendoza is a distinguished professional in the technology and financial sectors, with over three decades of experience in leadership roles and systems development. He demonstrates exceptional skill in integrating technological solutions into complex business operations. Throughout his career, José has led a variety of innovative projects, excelling in the implementation of biometric systems and customer identification platforms that have transformed banking and retail operations in various countries. His commitment to continuous technological advancement and his ability to adapt new technologies to business demands highlight his strategic vision and executive competence. José contributes not only his vast technical knowledge but also his practical experience in process optimization and the application of strategic technologies, which is essential for companies in the technology and financial sectors aspiring to lead in a highly competitive market.

Román Alejandro Mendoza Urdiales, Quantum Analytics, Sinaloa, Mexico

Román Mendoza is a leader in the artificial intelligence industry within consulting, working on developing solutions, strengthening capabilities, and generating knowledge in the field. His work focuses on delivering cutting-edge projects that integrate big data analytics and natural language processing to drive data-driven decision-making. With a solid track record of over 12 years in consulting projects, Román has specialized in implementing advanced technologies for operations research.

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