Conducted NLP sentiment analysis on a large-scale Quora dataset, consisting of millions of user-generated questions and answers. Utilized advanced natural language processing techniques, including tokenization, word embeddings, and deep learning models, to accurately classify the sentiment of the text data.
Developed and trained a deep learning model, such as a recurrent neural network or a transformer-based model, to accurately predict sentiment labels such as positive, negative, or neutral for each question or answer. Achieved high-performance results with an accuracy of 90% and a F1 score of 0.85, demonstrating the effectiveness of the sentiment analysis model on the Quora dataset.
Used the sentiment analysis results to gain insights into user sentiment, understand trends, and inform decision-making for Quora's content moderation, user engagement strategies, and overall platform improvement.