This repository contains Python implementations of text summarization, classification, and sentiment analysis algorithms using Twitter data. The goal of text summarization is to condense a large body of text into a shorter summary, while text classification is to distinguish positive and negative texts with the accuracy of 85% based on its content. Sentiment analysis is the task of determining the emotional tone of a piece of text, such as positive or negative.
Sentiment Analysis with Twitter Data To use the text summarization, classification, and sentiment analysis algorithms, you can simply clone the repository and run the corresponding Python file in the root directory. You will need to have a Twitter developer account and API keys in order to access Twitter data. You can modify the parameters of the algorithms, such as the number of desirable sentences in text summarizer.