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.
|Title of host publication||Proceedings of Sixth International Congress on Information and Communication Technology - ICICT 2021|
|Editors||Xin-She Yang, Simon Sherratt, Nilanjan Dey, Amit Joshi|
|Publisher||Springer Science and Business Media Deutschland GmbH|
|Number of pages||9|
|State||Published - 2022|
|Event||6th International Congress on Information and Communication Technology, ICICT 2021 - Virtual, Online|
Duration: 25 Feb 2021 → 26 Feb 2021
|Name||Lecture Notes in Networks and Systems|
|Conference||6th International Congress on Information and Communication Technology, ICICT 2021|
|Period||25/02/21 → 26/02/21|
Bibliographical notePublisher Copyright:
© 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
- Data mining
- Machine learning
- Social networks