I will do the text mining and sentiment analysis

I can work on Financial, Educational, Real Estate, Healthcare, etc. all major types of data set.

Text mining is the process of extracting meaningful insights from unstructured text data. Sentiment analysis determines whether the text expresses positive, negative, or neutral emotions.

I can analyze reviews, surveys, tweets, emails, customer feedback, articles, Reddit threads, or any other plain-text content.

Currently, I support English. For other languages, please message me first to confirm compatibility and tools.

Yes! Depending on the package, you’ll get charts like sentiment distribution, word clouds, frequency plots, and keyword graphs.

Yes. I can process large datasets efficiently. Please message me for a custom quote and delivery timeline if your data exceeds the standard limit.

Yes. I’ll share a clean, well-commented Python or R script (depending on your preference), so you can replicate or extend the analysis later.

I use Python libraries like NLTK, TextBlob, VADER, SpaCy, Transformers (BERT) and tools like Jupyter Notebook, Pandas, and Seaborn for visual output.

Absolutely. I can apply multi-class sentiment models (e.g., very positive, somewhat negative) or emotion classification (joy, anger, fear, etc.) upon request.

Yes. In Standard and Premium packages, you will receive a detailed PDF or Word Doc report with summaries, insights, and recommendations based on the analysis.