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Top Text Mining Software for Predictive Modeling

7 text mining software ranked by rating, review volume and listing quality.

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Between them, the 7 text mining software on this page cover graphical data presentation (6), text analysis (6), language detection (6) and taxonomy classification (6). 7 of them have written a profile you can read before you get in touch.

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  1. Cauliflower logo

    Cauliflower

    Graphical Data Presentation · Sentiment Analysis · Topic Clustering

    Cauliflower is a software platform for market research teams, built by a small team in Hamburg, Germany.

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  2. Etuma logo

    Etuma

    Graphical Data Presentation · Sentiment Analysis · Topic Clustering

    Etuma is a text analysis service for open-ended feedback. Its feedback tool, known as EFC, picks out the topics in each comment and the sentiment attached to them, using language…

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  3. SAS Text Miner logo

    SAS Text Miner

    Sentiment Analysis · Topic Clustering · Language Detection

    SAS Text Miner is a text mining product from SAS, an analytics and AI software company. It turns unstructured documents into material that can be analysed alongside other data.

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  4. WordStat logo

    WordStat

    Graphical Data Presentation · Sentiment Analysis · Topic Clustering

    WordStat is a text analytics program that helps researchers and organisations work through very large volumes of written material.

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  5. MonkeyLearn logo

    MonkeyLearn

    Graphical Data Presentation · Sentiment Analysis · Topic Clustering

    MonkeyLearn is an artificial intelligence platform for analysing text.

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  6. Customer Support Tickets Analytics logo

    Customer Support Tickets Analytics

    Graphical Data Presentation · Sentiment Analysis · Topic Clustering

    Customer Support Tickets Analytics is the product description for Cx MOMENTS, a tool used by customer support managers.

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  7. DiscoverText logo

    DiscoverText

    Graphical Data Presentation · Sentiment Analysis · Topic Clustering

    DiscoverText is a web-based system for analysing text collaboratively.

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