Web platform for the identification and analysis of events on Twitter and its influencers

Silva J.; Vargas J.; Cabrera D.; Carlos L.; Vigo E.; Pineda O.B. · Procedia Computer Science (2020) · DOI: 10.1016/j.procs.2020.03.052

Resumen

This article presents the results of the research carried out based on the extraction of a large volume of data from the UBER case in Colombia. The research on the #UberSeQueda phenomenon addresses different aspects in which transparency and democratization of information are the result of the use of Twitter; a computational process is applied to extract influential actors from the messages sent. It is concluded, from the use of graphs, that the preponderance of the actors involved in a social movement based on social networks constantly changes in short periods of time and that it is necessary to combine methods that involve both the user's profile and the current context.

Instituciones: Universidad Peruana de Ciencias Aplicadas