@misc{10481/106841,
year = {2025},
month = {8},
url = {https://hdl.handle.net/10481/106841},
abstract = {Text classification is essential for handling the large volume of user-generated textual content in social networks. Nowadays, dense word representation techniques, especially those
yielded by large language models, capture rich semantic and contextual information from
text that is useful for classification tasks, but generates high-dimensional vectors that hinder
the efficiency and scalability of the classification algorithms. Despite this, limited research
has explored effective dimensionality reduction techniques to balance representation quality with computational demands. This study presents a deep learning-based framework for
enhancing text classification in social networks, focusing on computational performance,
by compressing high-dimensional text representations into a low-dimensional space while
retaining essential features for text classification. To demonstrate the feasibility of the
proposal, we conduct a benchmarking study using traditional dimensionality reduction
techniques on two widely used benchmark datasets. The findings reveal that our approach
can substantially improve the efficiency of text classification in social networks without
compromising—and, in some cases, enhancing—the predictive performance.},
organization = {MCIN/AEI/10.13039/501100011033 y ERDF/EU
(PID2021-123960OB-I00)},
organization = {MCIN/AEI/10.13039/501100011033 y European Union — NextGenerationEU/PRTR
(TED2021-129402BC21)},
organization = {Consejería de Transformación Económica, Industria, Conocimiento y Universidades — Junta de Andalucía
(PREDOC_00298)},
publisher = {MDPI},
keywords = {Dimensionality reduction},
keywords = {Deep learning},
keywords = {Social media mining},
title = {Optimising Text Classification in Social Networks via Deep Learning-Based Dimensionality Reduction},
doi = {10.3390/electronics14173426},
author = {Díaz García, José Ángel and Morales Garzón, Andrea and Gutiérrez-Bautista, Karel and Martín Bautista, María José},
}