Track: Modeling and Simulation
Abstract
With the advancement of technology, Filipinos have a means of connecting to social media mainly to share what they are doing or what they feel now. This could lead to people venting out their stress on platforms such as Twitter. One of the topics that cause people a lot of stress is Politics and many social media users share their opinions in a stressful manner on Twitter. This paper will focus on detecting the reason for stress called stressors from the tweet. This will be done by collecting tweets based on their hashtags and NLP technique called topic modeling specifically LDA to form the topic of stress for stress detection. Then Machine learning algorithms of SVM, XGBoost, and Logistic Regression will be used on the tweets and topics created by the Topic modeling to create and train a model that can predict stressors based on the tweets and topics.