Apply Sentiment Analysis to any data using a single no-code application.
Sentiment analysis is an essential ML technique to classify the emotions found within the unstructured text.
Product reviews, customer surveys, employee feedback, chat messages, customer support tickets, call center audio files, and discussion boards contain free-form text which needs to be analyzed for sentiments. Sentiments can be classified into positive and negative with varying levels of confidence scores.
Applying sentiment analysis on large volumes of text on a near-real-time basis is challenging due to the data clean-up required to get text into an ML pipeline for analysis and reviews. Now there is an application with the required ML processing available to do just that for business managers. No IT Engineer or Data Scientist is required.
Enter SearchBlox PreText NLP.
You can set up sentiment analysis on any data source including webpages from a site, specific columns from a database, tweets, CSV records, or entire documents. And more importantly, everything can be done without writing a single line of code.
Once the data is processed, it is available for search and filtering by positive or negative sentiments on any data even across web pages, tweets, documents, emails, CSV, or database records. You can also create and process multiple data collections to review multiple sources of text data.
SearchBlox Enterprise Search with PreText NLP enables you to either host the application on your internal data center or utilize the fully managed cloud setup with nothing to install.
What are you waiting for? Let’s get started now.
