Sentiment Analysis for stack exchange data

Sentiment analysis is done by using posts and comments posted by users of a platform. The sentiment analysis approach is using to check which are the positive posts, that can be recommended for a user and to identify which are the negative posts. For this, as the first step data preprocessing techniques should be used to construct the data. Then feature extraction and training a model using the machine learning algorithm. Then check the positivity and negativity of the posts.

For the research paper of the analysis: https://github.com/DilsiChandrasena/Sentiment-Analysis/blob/main/Sentiment%20Analysis%20for%20stack%20exchange%20data.pdf