Being Data-driven, you must go beyond just gathering data, you need sentiment mining to extract and apply high-value intelligence, and for that, you need to have the access to a reliable sentiment analysis tool like Bytesview.
Here are the most important aspects you should look out for in a sentiment analysis tool-
Bytesview has them all, however, keep these points in reference while choosing a sentiment analysis tool, hope my answer helped you.
Certainly! Here are a few suggestions for finding annotated datasets for sentiment analysis in the customer support domain:
Twitter Sentiment Analysis Datasets: Twitter is a popular platform for customer support interactions. Look for datasets that specifically focus on sentiment analysis of customer support tweets. Some examples include the SemEval-2019 Task 5 dataset or the Sentiment140 dataset.
Customer Review Datasets: Explore datasets that contain customer reviews of products or services. Websites like Amazon, Yelp, or TripAdvisor often provide publicly available review datasets that can be used for sentiment analysis in the customer support context.
Customer Support Forums: Consider scraping or collecting data from customer support forums where users discuss their experiences and interactions with customer support representatives. Websites like Reddit or Stack Exchange may have relevant datasets that can be used for sentiment analysis.