Development of a classification system on big data set using machine learning techniques

Abstract

In this day and age, there are millions of people all around the world who are regular users of online social media platforms like Facebook, Twitter and Reddit. This has resulted in a huge amount of text data to be available online and is a good opportunity to be used to study and analyse sentiments of texts. This project aims to create classification models based on a Twitter dataset to classify Tweets to their sentiment class of either positive, negative, or neutral. 7 different classification models were explored and tuned to obtain accuracies ranging from 55%-70%. A Telegram bot that can output the sentiment of user inputs by using the trained classification models was made. By using Twitter APIs to stream Tweets, a real-time graph was also made which shows sentiment over time of a specified keyword.