Los Datos de X en la Investigación Científica: Tendencias y Desafíos

Lucía Rivadeneira; Ignacio Loor

doi:10.4185/rlcs-2025-2418

Authors

Lucía Rivadeneira Universidad Técnica de Manabí https://orcid.org/0000-0001-5989-7703
Ignacio Loor Universidad Técnica de Manabí https://orcid.org/0000-0003-4806-1032

DOI:

https://doi.org/10.4185/rlcs-2025-2418

Keywords:

social media, Twitter, X, research, trends

Abstract

Introduction: The growth of social media, especially X (formerly Twitter), has become a key resource for scientific research. This literature review identifies the factors driving its use, forecasts trends, and addresses challenges faced by researchers. Methodology: The review, based on a systematic search in Scopus, employed thematic mapping to identify interdisciplinary applications, methodological innovations, and the impact of global events. Key among these innovations was natural language processing (NLP) for data analysis, which grew 268% from 2019 to 2023. Results: NLP has established itself as a vital tool. However, publications based on X data showed a slowdown between 2021 and 2023, while Instagram and TikTok-based publications accelerated, signaling increased interest in these platforms. X remains the most used platform, followed by Facebook. Conclusions: The review highlights the need for more advanced analysis methods, stronger ethical standards concerning privacy and consent, and interdisciplinary approaches in social media research.

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Author Biographies

Lucía Rivadeneira, Universidad Técnica de Manabí

Lucía Rivadeneira holds a Ph.D. in Business and Management from the University of Manchester, United Kingdom; a Master's degree in Information Systems from Nanyang Technological University, Singapore; and a degree in Systems Engineering from the Technical University of Manabí, Ecuador. She is currently a lecturer and researcher at the Faculty of Computer Science, Technical University of Manabí, where she specializes in the analysis of social media data for modeling social phenomena. Her areas of interest include artificial intelligence, machine learning, unstructured data analysis, sentiment analysis, social network analysis, and classification and optimization models.

Ignacio Loor, Universidad Técnica de Manabí

Ignacio Loor holds a Ph.D. in Human Geography from the University of Manchester, United Kingdom; a Master's degree in International Business from Nova Southeastern University, United States; and an Economics degree from the Universidad Católica Santiago de Guayaquil, Ecuador. He currently works as a researcher in urbanism and sustainable development and as the Vice Dean of Research at the Faculty of Humanistic and Social Sciences at the Technical University of Manabí, Ecuador. His areas of interest include informal settlement infrastructure, green infrastructure, social organization of informal communities, informal practices, and the transition to net zero carbon emissions.

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