COVID-19 Spanish Sentiment Polarity Analyzer (2025)
Multimodal model (BETO + Vision Transformer) for polarity analysis of Spanish social-media posts about COVID-19, reaching a 96% F1 score.
Multimodal model (BETO + Vision Transformer) for polarity analysis of Spanish social-media posts about COVID-19, reaching a 96% F1 score.
Multimodal model (BETO + Vision Transformer) analyzing Spanish social-media sentiment around Saúl «Canelo» Álvarez’s fights, reaching a 77.76% F1 score.
A YOLOv8 / Ultralytics model to detect text embedded in images, such as memes in social-media posts.
New phishing-detection models for email, including a multilabel model that detects persuasion principles in English with LLMs.
Social-network analysis of the 2023 International Women’s Day movement on Twitter: community detection, temporal analysis, sentiment, and user classification.
Multilabel models to automatically classify human-rights recommendations from intergovernmental organizations using LLMs.
Opinion mining on Twitter (now X) via the Twitter API to model electoral preferences.
Analyzing Mexico’s image abroad from news and social-media sources via APIs; fine-tuned LLMs improved F1 by ~14% over previous work.
Collection and analysis of mining-activity reports from alternative digital sources across Latin America (2010–2022).