Sentiment analysis Bancolombia
DOI:
https://doi.org/10.26507/paper.4521Keywords:
sentiment analysis, machine learning, customer perception, BancolombiaAbstract
Sentiment analysis has become a key tool in data mining and natural language processing (NLP), allowing the evaluation of opinions and emotions expressed by users on digital platforms. In the financial sector, this type of analysis is especially relevant due to the strong influence that customer perception has on the reputation and positioning of banking institutions.
This article presents a sentiment analysis study applied to user comments posted on social media, specifically regarding the new mobile application launched by Bancolombia. Using machine learning techniques and textual analysis tools, the comments were classified into sentiment categories to identify patterns and trends in user perception. The results offer a detailed view of customer experiences and serve as a valuable resource for improving user interface design, customer service strategies, and digital communication practices.
Author Biographies
Karen Milena Rodríguez Díaz, Universidad Santo Tomás
Industrial Engineering student at the University of Santo Tomas
sixth semester
Ernesto Mendieta Sabogal, Universidad Santo Tomás
Professor at the University of Santo Tomas
References
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Bancolombia. (2024). Historia y evolución institucional. Recuperado el 22 de abril de 2025 de https://www.grupobancolombia.com/corporativo/conocenos/historia
Facebook Bancolombia. (2024). Comentarios de clientes extraídos de publicaciones oficiales. Consultado el 10 de abril de 2025 en https://www.facebook.com/Bancolombia
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Copyright (c) 2025 Asociación Colombiana de Facultades de Ingeniería - ACOFI
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
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