We commend six members of Batch 2021 who have successfully fulfilled the requirements of their senior high school capstone project (SHS-CSP), collaborating to create a prototype Filipino fake news detector to address the problem of misinformation.
Andrei Nicolas De Luna
Francis Nathe Omaña
Inigo Raphael De Leon
John Robertson Despi
Steven Miguel Herrera
Vito Alejandro Martin
Recognizing the need to efficiently spot fake news written in the Filipino language, the six-member team produced a novel way to detect fake news through natural language processing (NLP) – a model that uses a simple machine learning algorithm to study thousands of real news and fake news and classify text-based news articles based on the concept of a probabilistic Multinomial Naïve Bayes classifier – following months of research. The classifying approach, which does not require graphic or tensor processing units, has an accuracy metrics of 94%, with a 12.9 millisecond training time. For future studies on the field, the researchers recommend that bigger news data sets be considered as well as the integration of the fake news detection model with non-text medium such as video and image.
ANIMO La Salle Green Hills!
