Twitter Sentiment Analysis

Abstract

Twitter Sentiment Analysis is the process of extracting opinions, sentiments, and emotions expressed in tweets. This analysis can be used to determine the overall public opinion on a particular topic or to gauge the sentiment of customers towards a product or service. We use Textblob to classify tweets as positive, negative or neutral based on their content. We start by collecting a dataset of tweets using the Twitter API and manually labelling them as positive, negative or neutral. We are doing preprocess the text by removing stop words, punctuation, and special characters, and convert the text into a bag-of-words representation. We then use Textblob to train a model on the preprocessed data and test it on a separate set of tweets. Keyword: Textblob, twitterdataset, Twitter sentiment analysis