LDA Algorithm for the Identification of Topics: A Case of Study in the Most Influential Twitter Accounts in Ecuador

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Resumen

In the last years, the environment in which we develop has had various changes, most of them due to major technological changes, and the constant development of Information and Communication Technologies (ICTs). As a result of the advances in ICTs, today it is common to interact through social networks and make constant use of them. For this reason, this paper presents an analysis of the 10 most influential Twitter accounts in Ecuador; the objective of this analysis is to detect what the topics or topics addressed in these accounts are. The Latent Dirichlet Allocation (LDA) algorithm using bag of words (BoW) model and also the Term Frequency–Inverse Document Frequency (TF-IDF) model were used for the analysis, finally finding, if the topics provided by both models are similar.

Idioma originalInglés
Título de la publicación alojadaProceedings of Sixth International Congress on Information and Communication Technology - ICICT 2021
EditoresXin-She Yang, Simon Sherratt, Nilanjan Dey, Amit Joshi
EditorialSpringer Science and Business Media Deutschland GmbH
Páginas359-367
Número de páginas9
ISBN (versión impresa)9789811617805
DOI
EstadoPublicada - 2022
Evento6th International Congress on Information and Communication Technology, ICICT 2021 - Virtual, Online
Duración: 25 feb. 202126 feb. 2021

Serie de la publicación

NombreLecture Notes in Networks and Systems
Volumen216
ISSN (versión impresa)2367-3370
ISSN (versión digital)2367-3389

Conferencia

Conferencia6th International Congress on Information and Communication Technology, ICICT 2021
CiudadVirtual, Online
Período25/02/2126/02/21

Nota bibliográfica

Publisher Copyright:
© 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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