DESIGN AND DEVELOPMENT OF SOCIAL MEDIA SENTIMENT ANALYSIS ON CUSTOMER REVIEWS OF AMAZON PRODUCTS FOR BUSINESS INTELLIGENCE IN PYTHON

Abstract

Social media is used by people to communicate, share, and consume information in today's rapidly evolving technological environment. In order to give corporate intelligence a convenient and cohesive platform, social media mining combines social media, social network analysis, and data mining. The proposed social media sentiment analysis advocates Python in developing the sentiment model. In the proposed model, the CountVectorizer and TF-IDF (Term Frequency-Inverse Document Frequency) are used for feature extraction in natural language processing. The machine learning algorithms Random forest and logistic regression are used to calculate the dataset's accuracy and correctness. The suggested sentiment analysis's findings and insights provide insightful business intelligence that can help the organization grow.