I’m completing my MTech at GTU and my approved thesis topic is sentiment analysis of hotel reviews collected from major online review websites such as TripAdvisor and Booking.com. I need a data-savvy NLP partner who can work with me across the full research pipeline—from harvesting the raw reviews to writing up publish-ready results. Here’s what I have in mind: • Build and share a reproducible scraper or API workflow that gathers a sizeable, legally usable corpus of hotel reviews (ideally 50 000+). • Clean, label, and explore the text so we can isolate meaningful sentiment signals; I’m open to focusing on customer satisfaction, service quality, room amenities, or any mix that produces the most insightful output. • Develop both baseline keyword approaches and more advanced machine-learning or deep-learning models in Python (NLTK, scikit-learn, TensorFlow/PyTorch—whatever fits best). An F1 score of 0.80+ on a held-out test set is our performance target. • Visualise findings and convert them into thesis-ready tables, figures, and discussions that comply with the GTU format. • Deliver well-commented code/notebooks, the cleaned dataset, and chapter drafts (methodology, experiments, results, conclusion) along with a brief walkthrough so I can reproduce everything on my own laptop. Timeline is tight: first data pull within a week, full experimental results in roughly six weeks, and a final polished document shortly after. If you’ve handled similar sentiment projects and can guide me through to a successful defense, let’s get started right away.