Consultant Intern
- Sentiment Analysis Project Execution: Collected and analyzed online reviews of vehicle models for an automotive client. Using data analysis and algorithmic techniques, identified and categorized customer feedback attitudes. Provide recommendations to help the client better understand market demand and key customer complaints, by integrating large language model-generated insights,
- Automated Data Collection and preparation: Developed codes with Python and the Selenium package to scrape user text reviews from major automotive websites and store them in a MongoDB database. Also breaking down text into individual words or phrases and removing irrelevant characters, making it suitable for sentiment analysis.
- Preliminary Analysis and Visualization: Counting occurrences of specific keywords related to positive, negative, or neutral sentiments to identify common themes or customer concerns. Then use word clouds, frequency distribution plots to identify trends or patterns.
- Sentiment Analysis: help and learn to leverage a large language model (GPT-3) to perform sentiment analysis and public opinion forecasting on textual data.