Survey Sentiment Analysis & Sinhala Translation
Budget: $2 – $8 USD
I have a CSV file that contains the verbatim responses from a recent customer-feedback survey. I need two things completed on this data set:
1. A clear sentiment analysis that shows the overall tone (positive, negative, neutral) of each response and an aggregated summary of trends you spot.
2. An accurate translation of every comment into Sinhala so I can share the findings with our local team.
You are free to choose the tool you prefer—Python with pandas/text-blob, R, or any dependable NLP platform—as long as the final deliverables open cleanly in Excel and Word. If you require additional preprocessing steps, let me know and I can supply any extra information you might need about coding frames or product names that appear in the text.
Deliverables I’m expecting:
• An updated Excel workbook with the original comment, its detected sentiment score or label, and the Sinhala translation side-by-side.
• A concise Word report (2–3 pages) summarising key insights, notable themes, and any actionable recommendations that emerge from the analysis.
Accuracy in both the linguistic translation and the statistical sentiment scoring is essential; I will sample-check a subset in Sinhala to confirm quality. If you have examples of similar sentiment projects, feel free to mention them when you respond.
1. A clear sentiment analysis that shows the overall tone (positive, negative, neutral) of each response and an aggregated summary of trends you spot.
2. An accurate translation of every comment into Sinhala so I can share the findings with our local team.
You are free to choose the tool you prefer—Python with pandas/text-blob, R, or any dependable NLP platform—as long as the final deliverables open cleanly in Excel and Word. If you require additional preprocessing steps, let me know and I can supply any extra information you might need about coding frames or product names that appear in the text.
Deliverables I’m expecting:
• An updated Excel workbook with the original comment, its detected sentiment score or label, and the Sinhala translation side-by-side.
• A concise Word report (2–3 pages) summarising key insights, notable themes, and any actionable recommendations that emerge from the analysis.
Accuracy in both the linguistic translation and the statistical sentiment scoring is essential; I will sample-check a subset in Sinhala to confirm quality. If you have examples of similar sentiment projects, feel free to mention them when you respond.
Related categories:
Python
Translation
Data Processing
Excel
Statistics
Data Analysis
Natural Language Processing
Sentiment Analysis