Chew You Shen School Of Computer Sciences, Universiti Sains Malaysia
Twitter plays an important role in Malaysia’s politics as more Malaysian politicians and users use it to express their political views. However, despite thousands of political tweets are being posted on the platform on a daily basis, less effort has been put into extracting political insights from the Malay tweets. Existing solutions only provides political analysis in the form of report and articles. Public could only view analysis that are only made available to them. Hence, politicians and political parties may be unaware of people’s opinion towards them within a short amount of time. The main objectives of this project includes retrieve Malay tweets related to Malaysia politics and politicians from Twitter, uncover relevant topics automatically and its corresponding keywords from Malay tweets, create sentiment and emotion detection models based on Malay tweets and display visualized political insights. This application MYPolitics can collect political tweets from Twitter and perform sentiment and emotion analysis on the Tweet using deep learning method: Long Short-Term Memory (LSTM) Model. It can also uncover the topics and its keywords from netizen and politician’s tweet using Latent Dirichlet Allocation (LDA) algorithm. whereas the data visualization module will display the political insights using various form of visualizations. This project aligns with SDG 16 Peace, Justice and Strong Institution. This SDG can be achieved by promoting peaceful and inclusive societies for sustainable development, provide access to justice for all and build effective, accountable and inclusive institutions at all levels through raising political awareness among the public in Malaysia.