Sentiment analysis plays a great role in our lives today. As social media plays a bigger and bigger role in our lives today, the number one factor for consumers when buying a product is to hear what others need to say. This has become a great area to develop for a content marketing strategy as they can use social content to understand what people feel about products. Another aspect of sentiment analysis is to removing content that may be inappropiate by using machine learning to evaluate the context and sentiment.
The goal for this hackathon was to use sentiment analysis to detect the sentiment of a tweets database. I have tried 2 popular methodoligies for sentiment analysis which are: neural networks and logistic regression.
DivisionSigma.ipynb-Contains the code used for sentiment analysis, with comments on the steps.
final (2).csv-The results after feeding the initial data through the model.