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

Jesus Silva | Zendy; Jesús Vargas | Zendy; Danelys Cabrera | Zendy; Lourdes Carlos | Zendy; Emperatriz Vigo | Zendy; Omar Bonerge Pineda | Zendy

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

Author(s) -

Jesus Silva,

Jesús Vargas,

Danelys Cabrera,

Lourdes Carlos,

Emperatriz Vigo,

Omar Bonerge Pineda

Publication year - 2020

Publication title -

procedia computer science

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.334

H-Index - 76

ISSN - 1877-0509

DOI - 10.1016/j.procs.2020.03.052

Subject(s) - computer science , influencer marketing , transparency (behavior) , social media , process (computing) , identification (biology) , democratization , context (archaeology) , data science , world wide web , phenomenon , data mining , computer security , democracy , paleontology , botany , physics , marketing , quantum mechanics , politics , relationship marketing , political science , law , business , biology , marketing management , operating system

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.

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