A sentiment analysis of public perception on Malaysia general election using Naive Bayes / Nur Hidayah Athira Sahrul Afendi

Twitter has been prominently used during the electoral campaigns. Twitter helps the politicians to spread and share their political agenda. Through Twitter, every information is accessible to anyone and anybody around the world in keeping up with the information and opinion about the general election that happening in Malaysia. This study aims to analyze the public perception on Malaysia general election via Twitter. This study employed a Naive Bayes Classification to get the data whether it is positive, or negative. Specifically, Naive Bayes used for sentiment analysis for the English tweets. Top trending hashtags were used to fetch tweets resulting in 11816 tweets. The method used by using Apify to collect the data and save it into CSV file.