New Release of CoreText Analytics includes Sentiment Analysis Capabilities

Quester is pleased to announce a new release of CoreText Analytics  –  our text analytics software which has been enhanced with a sentiment analysis feature.

Introduced on a SaaS platform in July 2018, CoreText Analytics gives users the ability to import verbatim responses from an entire dataset and quickly produce a report highlighting the most prevalent themes and ideas represented in the data. The software is used by companies to analyze customer reviews, survey responses, social media posts and other sources where consumer opinions are collected. In this latest release, users can also gauge the overall sentiment of respondents by directionally grouping verbatims based on positive and negative language.

Language databases collected and analyzed by Quester researchers provide the foundation for the software upgrade which is essentially a “sentiment dictionary” capable of making a judgement call as to whether a response is positive or negative — an essential capability given the nuances of language and the importance of context. The core of the system has been developed based on historic emotional research, with the overlay of Quester’s decades of experience parsing positive and negative responses.

The phrase “more convenient” provides one example of the sentiment analysis tool in action. As a stand-alone, it has a positive connotation. But while one consumer may respond that a restaurant’s proposed new location “is more convenient for me,” another may use the same phrase but feel altogether differently, as in the response, “It isn’t any more convenient for me.” CoreText Analytics can sort and group the idea of “convenience” in a dataset, then further sort responses for positive or negative meaning.

“This CoreText upgrade has actually been years in the making,” says Quester president, Tim Hoskins. “The millions of interviews we’ve conducted over the past 15 years have been a goldmine for building the language libraries that inform the sentiment analysis feature. Mining data for consumer sentiment can be extremely time-consuming for researchers. With CoreText, a dataset can be accurately evaluated and coded at a faster rate than competing solutions.”

For a demonstration of CoreText and the new sentiment analysis feature, please contact us at

Leave a Reply

Your email address will not be published. Required fields are marked *

This site uses Akismet to reduce spam. Learn how your comment data is processed.