Lucas Raniére Juvino Santos
Ph.D., Developer and Researcher
About
I am a computer scientist with research interests spanning social computing, natural language processing, and machine learning, including political polarization on social media, fact-checking, intelligent agents, and applied computer vision. I currently work on Judo-AI, applying computer vision to combat sports.
Academic Experience
Ph.D. in Computer Science
- Research topics: political polarization and radicalization on social media networks.
- December 2023 – August 2024: Visiting Ph.D. Researcher at Indiana University (Bloomington, Indiana).
Master's Degree in Computer Science
- Research topics: experimental software engineering and software artifact traceability.
- Dissertation: Improving Traceability Recovery Between Bug Reports and Manual Test Cases.
Bachelor's Degree in Computer Science
- Research topics: text translation into sign language and digital inclusion of deaf people.
- Term paper: Use of Probabilistic Reasoning to Resolve Lexical Ambiguities in Portuguese.
Research Projects
Judo-AI — Applied Computer Vision for combat sports
- Computer vision
- Object detection
- Video segmentation
- Human action recognition
- Video understanding
Agents4Good — Intelligent Agents for Automatic Fact-checking
- Social computing
- AI agents
- LangChain and LangGraph
- Natural language processing
- Speech analysis
- Argument analysis
- Toxicity detection
Advanced Intelligent Channels — Applied ML for sales/support chat automation
- Natural language processing
- Machine learning
Publications
Beyond Verdicts: Explainable Fact-Checking via a Linguistically-Grounded Multi-Agent Framework
Accepted at ACM Hypertext and Social Media Conference (HT '26). To be presented September 2026.
Who Is Who in Judo? Role-Aware Detection in Match Video
Accepted at Encontro Nacional de Inteligência Artificial e Computacional (ENIAC '26). To be presented October 2026.
Can Large Language Models Effectively Mitigate Polarization in Social Media Text?
Proceedings of the 17th ACM Web Science Conference (WebSci '25). ACM, New York, NY, USA, 348–357.
Uniting Politics and Pandemic: a Social Network Analysis on the COVID Parliamentary Commission of Inquiry in Brazil
Proceedings of the Brazilian Symposium on Multimedia and the Web (WebMedia '22). ACM, New York, NY, USA, 99–107.
Improving Traceability Recovery Between Bug Reports and Manual Test Cases
Proceedings of the XXXIV Brazilian Symposium on Software Engineering (SBES '20). ACM, New York, NY, USA, 293–302.
Datasets and Models
Judo-AI 3 Classes Models (Weights from "best.pt")
Pre-trained YOLO object detection model weights for identifying three classes in judo matches: referee, blue athlete, and white athlete.
[Tweets] 2022 Brazilian Presidential Elections
A dataset of over 7 million tweets from 2022 collected to study political discourse during Brazil's presidential election.
[Tweets] 2023 Brazilian Early Political Events
A dataset of over 13.9 million Portuguese-language tweets from early 2023 for NLP and social network research on political discourse.
[Dataset] Tweets about COVID-19 Brazilian PCI
A dataset of roughly 3.4 million tweets collected over 26 weeks regarding Brazil's COVID-19 Parliamentary Commission of Inquiry.