DiscoverText: Text Analytics and Mining Software
DiscoverText helps data scientists and researchers analyze unstructured text from surveys, social media, and emails. It supports teams that combine human coding with machine-learning classifiers.
At a glance
- Category
- Data & Analytics
- Best for
- Data scientists, Market researchers, Legal teams, Academics, Students
- Pricing
- Free access is available through a free trial. Students and professors may receive free access and project support.
- Key use cases
- Customer Feedback Analysis, Social Media Research, Legal E-Discovery, Academic Research
- Official website
- discovertext.com
DiscoverText is a cloud-based platform designed to help users sort and analyze unstructured text data. It uses a point-and-click web interface for processing data from sources like customer feedback, social media, and government comments.
The tool is designed for a variety of users, including market researchers, legal teams, and academics. It supports the process of cleaning data and classifying it into topics or sentiments using a hybrid approach that combines human insight with machine-learning classifiers called sifters.
For legal professionals, the software includes document redaction capabilities. For data scientists, it offers tools for deduplication and automated clustering to help identify patterns in large datasets.
Buyers should confirm if their specific data sources are compatible with the platform's upload methods and whether the annotation workflow fits their internal team structure.
Key Features
Supports the analysis and mining of text data across multiple languages.
Allows users to build reusable classifiers to sort text into specific topics or sentiment categories.
Supports a hybrid workflow where humans code text to help train machine-learning models.
Identifies near-duplicate text entries to help users understand the data landscape.
Supports the removal of sensitive information such as names and email addresses from documents.
Helps data teams identify which items in a collection may provide the most value for human coding.
Use Cases
Collecting and cleaning unstructured text from surveys, emails, and feedback platforms.
Mining and classifying data from X (Twitter) and RSS feeds to track digital footprints.
Using document redaction to produce Bates-stamped and indexed PDF collections.
Supporting scientific research and qualitative data analysis for scholarly publications.
Best For
Pricing
Free access is available through a free trial. Students and professors may receive free access and project support.
FAQ
It is designed for data scientists, market researchers, legal teams, academics, and students who need to analyze unstructured text.
The platform provides free access with a free trial, and offers free access and training to students and professors.
It can process unstructured text from surveys, social media (such as X/Twitter), emails, customer feedback, and government comments.
Source category: Data & Analytics
Source subcategory: Analytics & Reporting
