Impacto de la red social Twitter en la imagen de Colfondos S.A.
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Date
2022-06-24
Advisors
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Publisher
Corporación Universitaria Minuto de Dios
Type
Thesis
Rights
Atribución-NoComercial-SinDerivadas 2.5 Colombia
Abstract
En la última década se ha incrementado el interés por el manejo de grandes cantidades de información y la extracción de conocimiento por medio de las redes sociales, las cuales han jugado un papel muy importante en la sociedad debido a la fácil interacción e intercambio de opiniones acerca de un tema determinado. Esto hace de estas plataformas una gran fuente de información para las empresas, aprovechar dichos datos e interpretarlos de una manera ágil y eficiente; todo ello con el fin de mejorar sus estrategias de mercadeo y optimizar la toma de decisiones.
Este proyecto se encuentra enmarcado dentro de la minería de texto y el procesamiento del lenguaje natural; cuyo objetivo será desarrollar un modelo de clasificación para el análisis de sentimientos en Twitter, permitiendo conocer la percepción de los usuarios de esta red acerca del sistema pensional colombiano y los fondos privados de pensiones del país.
Finalmente se muestran los resultados del análisis por medio de un tablero de control donde se complementa con métricas utilizadas para el seguimiento regular de la red social.
In the last decade, there has been an increase in interest in managing large amounts of information and extracting knowledge through social networks, which have played a very important role in society due to the easy interaction and exchange of opinions about of a certain topic. This makes these platforms a great source of information for companies, leading them to take advantage of data and interpret it in an agile and efficient manner, in order to improve their marketing strategies and optimize decision-making. This project is framed within text mining, natural language processing and machine learning; whose objective will be to develop a classification model that allows an analysis of sentiments on Twitter, allowing to know the perception of the users of this network about the Colombian pension system and the country's private pension funds. Finally, the results of the analysis are shown through a control panel where they are complemented with metrics used for regular monitoring of the social network.
In the last decade, there has been an increase in interest in managing large amounts of information and extracting knowledge through social networks, which have played a very important role in society due to the easy interaction and exchange of opinions about of a certain topic. This makes these platforms a great source of information for companies, leading them to take advantage of data and interpret it in an agile and efficient manner, in order to improve their marketing strategies and optimize decision-making. This project is framed within text mining, natural language processing and machine learning; whose objective will be to develop a classification model that allows an analysis of sentiments on Twitter, allowing to know the perception of the users of this network about the Colombian pension system and the country's private pension funds. Finally, the results of the analysis are shown through a control panel where they are complemented with metrics used for regular monitoring of the social network.
Description
Analizar patrones y tendencias de las publicaciones realizadas en Twitter donde se mencionen las AFP privadas en Colombia, con el fin de aportar herramientas a las estrategias de mercadeo y fidelización de Colfondos.
Keywords
Twitter, Análisis de sentimientos, Aprendizaje automático, Big Data, Twitter, Sentiment analysis, Machine learning, Pensions, Big Data