One of the techniques that is used to investigate the relationship of people with respect to a specific topic in the field of big data is text mining, which is basically using words or texts with the purpose of inferring robust analysis of a situation. This article presents a text analysis of the interactions on Twitter among candidates and followers during the last four days of Bogotá mayoral campaign 2019, with the purpose of analyzing the level of acceptance that followers have of the publications of the candidates regarding their campaigns during this period prior to the voting exercise. We used the text analysis technique, for which the trills of the followers of the candidates for Mayor of Bogotá were extracted using the statistical software R-Studio and API. The results show four graphs corresponding to the word frequency of the followers of each candidate. It begins with candidate Miguel Uribe, followed by candidate Carlos Galán, then candidate Hollman Morris, and finally candidate Claudia López, showing that the more diverse the colors and the larger the word size, the more frequent the use of words, which generates greater communication between the candidate and the supporters to promote the campaigns.
