Sentiment Analysis Using Machine Learning Algorithm

Abstract- Naive Bayes sentiment analysis, which includes sentiment analysis on abstracts, is a well-liked method for text classification. A probabilistic technique called the Naive Bayes generates predictions about the likelihood that a document will fall into a specific category. In sentiment analysis, the algorithm determines if a text has a positive, negative, or neutral sentiment based on the likelihood that it does. The first step in performing sentiment analysis using Naive Bayes on abstractions is to preprocess the text by eliminating any extraneous details like punctuation and stop words and changing all of the words to lowercase.

The method determines the sentiment of the document by choosing the sentiment category with the highest probability after calculating the probabilities for each sentiment category. Overall, sentiment analysis with Naive Bayes on abstracts can be a useful method for categorizing the tone of written content. It can be applied to a range of tasks, such as social media monitoring, customer feedback analysis.