Two papers accepted at the ICPRS´22

Dr. Márjory da Costa Abreu has the papers Exploring Content-Based and Meta-Data Analysis for Detecting Fake News Infodemic: A case study on COVID-19 and Exploring Bias Analysis on Judicial Data using Machine Learning Techniques accepted at the 12th International Conference on Pattern Recognition Systems.

The paper Exploring Content-Based and Meta-Data Analysis for Detecting Fake News Infodemic: A case study on COVID-19 presents an analysis of using a combination of classical machine learning models and deep learning techniques as well as a selection of descriptive text features to identify fake news related to COVID-19 on social media. This research is the result of the work developed by Ashish Garg (MSc Big Data Analytics - SHU).

The paper Exploring Bias Analysis on Judicial Data using Machine Learning Techniques presents an analysis of using classical machine learning models to identify bias in judicial sentences is the result of the work developed by Bruno Silva (MPhil in Systems and Computing - UFRN/Brazil).