MTech Thesis: Hotel review Sentiment Analysis
Budget: ₹1,500 – ₹12,500 INR
I’m ready to start my M-Tech dissertation and need a complete, end-to-end research package on hotel-review sentiment analysis. The study must begin with a concise literature survey of at least five peer-reviewed papers published over the past three years in IEEE, Springer or comparable journals. I expect a clear synthesis that pinpoints the research gap these papers leave open.
Once the gap is documented, I’ll need a straightforward research objective built around it, followed by a practical dataset plan (publicly available, lightly pre-processed or newly scraped—whichever best suits the gap you identify). From there, design an appropriate model and fully describe the experimental methodology; simplicity and reproducibility are more important than pushing state-of-the-art boundaries.
Key deliverables:
• 2-3 page critical literature review highlighting the gap
• Clear research question and hypothesis aligned to that gap
• Dataset description or collection script with annotation guide
• Model architecture choice with rationale (code in Python preferred)
• Step-by-step methodology, evaluation metrics and expected outcome format
• Draft thesis chapters in editable Word/LaTeX, ready for advisor feedback
Acceptance criteria: the gap must be traceable back to the five selected papers, the dataset must be obtainable without paid licenses, and the baseline model must run end-to-end on a mid-range GPU or CPU within reasonable time.
If you’re comfortable shaping the topic and producing replicable results, let’s get started right away.
Once the gap is documented, I’ll need a straightforward research objective built around it, followed by a practical dataset plan (publicly available, lightly pre-processed or newly scraped—whichever best suits the gap you identify). From there, design an appropriate model and fully describe the experimental methodology; simplicity and reproducibility are more important than pushing state-of-the-art boundaries.
Key deliverables:
• 2-3 page critical literature review highlighting the gap
• Clear research question and hypothesis aligned to that gap
• Dataset description or collection script with annotation guide
• Model architecture choice with rationale (code in Python preferred)
• Step-by-step methodology, evaluation metrics and expected outcome format
• Draft thesis chapters in editable Word/LaTeX, ready for advisor feedback
Acceptance criteria: the gap must be traceable back to the five selected papers, the dataset must be obtainable without paid licenses, and the baseline model must run end-to-end on a mid-range GPU or CPU within reasonable time.
If you’re comfortable shaping the topic and producing replicable results, let’s get started right away.