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Big Data Sentiment Analysis

Twitter has 217 million daily active users. Social media usage is one of the most popular online activities. People tend to be more honest online due to anonymity and are more willing to express their opinions and emotions. Twitter is a treasure trove of data and analysing it will generate valuable insights both commercially and socially.

In this project, we plan to conduct sentiment analysis on Twitter users’ tweets. Sentiment analysis is a study on the public’s opinion towards an event or a product and it is a Natural Language Processing technique.

We will use data mining methods to produce a dataset of user's Tweets based on a specific topic of interest, for a given date range. Then, we will train our machine learning models using an established and balanced dataset, and use the models to generate the polarity of the given Tweet - whether it has positive or negative sentiment.

The results will tell us whether netizens in general think positively or negatively on the given topic, and provide a detailed breakdown showing our results.

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