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

被引：0

作者：

Silva, Jesus ^{[1
]}

Vargas, Jesus ^{[2
]}

Cabrera, Danelys ^{[2
]}

Carlos, Lourdes ^{[1
]}

Vigo, Emperatriz ^{[1
]}

Bonerge Pineda, Omar ^{[3
]}

机构：

[1] Univ Peruana Ciencias Aplicadas, Fac Negocios, Lima, Peru

[2] Univ Costa, Barranquilla, Colombia

[3] Univ Tecnol Centroamer UNITEC, San Pedro Sula, Honduras

来源：

11TH INTERNATIONAL CONFERENCE ON AMBIENT SYSTEMS, NETWORKS AND TECHNOLOGIES (ANT) / THE 3RD INTERNATIONAL CONFERENCE ON EMERGING DATA AND INDUSTRY 4.0 (EDI40) / AFFILIATED WORKSHOPS | 2020年 / 170卷

关键词：

social network analysis; graphs; influential actors; interdisciplinary;

D O I：

10.1016/j.procs.2020.03.052

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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. (C) 2020 The Authors. Published by Elsevier B.V.

引用

页码：1147 / 1152

页数：6

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