Sai Snehith Rachamalla

Meticulous Data Scientist accomplished in compiling, transforming and analyzing complex information through software. Expert in machine learning and large dataset management. Demonstrated success in identifying relationships and building solutions to business problems.

Project Name: Sentiment Analysis of Twitter Data Using Machine Learning and Semantic Analysis

Project Description:
This project focuses on analyzing sentiment from Twitter data using Machine Learning (ML) approaches and Semantic Analysis techniques. It aims to classify customer opinions into positive, negative, or neutral sentiments, which play a crucial role in decision-making processes.

The workflow involves data preprocessing, feature extraction, and sentiment classification. Key steps include:

• Extracting meaningful features from tweets using adjective-based feature vectors
• Applying Machine Learning algorithms such as Naïve Bayes, Maximum Entropy, and Support Vector Machines (SVM) for classification
• Enhancing accuracy using Semantic Orientation with WordNet, which identifies synonyms and contextual similarity

The system evaluates classifier performance based on precision, recall, and accuracy, ensuring reliable sentiment analysis. This project demonstrates the power of AI and NLP in understanding public opinion and can be applied to customer feedback analysis, brand monitoring, and social media trend insights.