Análisis de sentimientos a través de redes sociales para medir los niveles de aceptación de la universidad técnica estatal de quevedo

Social media has become a crucial channel for interaction and expression of opinions. However, many educational institutions face significant challenges in understanding their community's perceptions due to the lack of specialized tools to analyze emotions expressed on these platforms. This lim...

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Bibliografiske detaljer
Hovedforfatter: Coronado Bustos, Domenica Mariella (author)
Format: bachelorThesis
Sprog:spa
Udgivet: 2024
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Online adgang:https://repositorio.uteq.edu.ec/handle/43000/7935
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Summary:Social media has become a crucial channel for interaction and expression of opinions. However, many educational institutions face significant challenges in understanding their community's perceptions due to the lack of specialized tools to analyze emotions expressed on these platforms. This limitation hinders the identification of areas for improvement, affects institutional reputation and competitiveness, and restricts the ability to strategically respond to the expectations of students, alumni, and other stakeholders. Additionally, the high volume and diversity of data generated on social media present further challenges for effective processing and analysis.In response to this issue, the purpose of this project is to develop a methodology for analyzing sentiments on social media, providing a clear and measurable view of the institution's perception. By using tools such as web scraping for data extraction, the VADER algorithm for emotion classification, and SPSS for statistical analysis, comments and posts are categorized into positive, negative, and neutral sentiments. This approach aims to offer strategic insights to enhance the relationship with the university community and optimize the institution's image in the digital environment. The findings reveal relevant patterns, such as the predominance of interactions on social media and the association of negative sentiments with administrative issues, while positive sentiments are linked to academic quality and faculty engagement. Finally, a management plan is proposed based on these findings, with concrete actions to strengthen identified critical areas and foster more positive interactions. This methodology provides a replicable model for other institutions, demonstrating the importance of sentiment analysis as a tool to manage and improve institutional perception.