Resumo

MENDOZA MACIAS, José Guadalupe  e  MENDOZA URDIALES, Román Alejandro. Prioritizing the Net Sentiment Score: A Banking Industry Case Study. The Anáhuac j. [online]. 2024, vol.24, n.1, pp.272-293.  Epub 26-Ago-2024. ISSN 2683-2690.  https://doi.org/10.36105/theanahuacjour.2024v24n1.10.

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.

Palavras-chave : stock performance; net sentiment score (NSS); robust linear model regression; brand value impact.

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