Collaborative text analytics

With dozens of powerful text mining features, including access to free and premium Gnip Twitter data, DiscoverText provides software tools to quickly and accurately evaluate text data.

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Collect, clean, and analyze

Data is messy. Data scientists know that cleaning data can be very time consuming. Users of DiscoverText build custom machine classifiers or “sifters” to find the most relevant items. DiscoverText shortens a process that used to last weeks or months; our machine-learning sifters are created in hours or just a few minutes. We support technical integrations with Twitter and SurveyMonkey.

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Humans & machines learn together 

Humans are good at some things and computers are good at others. A consistent back and forth between humans and machines increases the ability of both to learn. Our software originates in a decade of NSF-funded research into the measurements that accelerate machine-learning.

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Cluster information automatically

Deduplication and automated clustering of near-duplicates gives users a high level sense of the data landscape. Interactive classifier histograms identify the items in a collection that add the most value when coded. These tools enable purposive sampling that further accelerates the active-learning process of training classifiers.

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Filters: The ultimate text analytics tool

Filter by date, geo, place name, influence, networks, or numerous other metadata values. Create and save complex search queries, human coding schemes, or just filter on active-learning machine classification scores. Stack multiple filters for highly refined yet easily accessible custom text analytics results. Our favorite filter is “items not coded” but there are many others that underscore why “all text analytics ultimately can be seen as filtering.” – Stu Shulman

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Keyword search, word clouds, and custom topic dictionaries

Discover central topics and also those elusive but valuable unexpected concepts. Use this information to train machine-learning classifiers to recognize relevant text and social media data. Jump into data using an interactive word CloudExplorer or build a mini topical dictionary using “defined” search.

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