WordStat is a flexible and easy-to-use text analysis software – whether you need text mining tools for fast extraction of themes and trends, or careful and precise measurement with state-of-the-art quantitative content analysis tools. WordStat‘s seamless integration with SimStat – our statistical data analysis tool – and QDA Miner – our qualitative data analysis software – gives you unprecedented flexibility for analyzing text and relating its content to structured information, including numerical and categorical data.

What it is used for?
WordStat can be used by anyone who needs to quickly extract and analyze information from large amounts of documents. Our content analysis and text mining software is used for:

• Content analysis of open-ended responses, interview or focus group transcripts
• Business intelligence and competitive web sites analysis
• Information extraction and knowledge discovery from incident reports, customer complaints
• Content analysis of news coverage or scientific literature
• Automatic tagging and classification of documents
• Fraud detection, authorship attribution, patent analysis
• Taxonomy development and validation

Key and Unique features
Powerful content analysis and text mining software for handling large amounts of unstructured information. WordStat can process up to 20 million words per minute and identify all references to user-defined concepts using categorization dictionaries.

Integrated exploratory text mining and visualization tools such as clustering, multidimensional scaling, proximity plots, and more, to quickly extract themes and automatically identify patterns.

Truly unique computer assistance for dictionary building with tools for extracting common phrases and technical terms and for quickly identifying in your text collection, misspellings, synonyms, antonyms and related words.

One click access to keyword-in-context and keyword retrieval tools for easy identification and coding of relevant text segments, validation of content analysis dictionaries, word-sense disambiguation or for drilling down to the source documents.

Seamless integration with a state of the art qualitative coding tool (QDA Miner), allows more precise exploration of data or more in-depth analysis of specific documents or extracted text segments when needed.

Machine Learning for automatic document classification using Naive Bayes and K-Nearest Neighbours algorithms with automatic features selection and validation tools. Classification models may then be saved on disk and reapplied on new data.

Easy importation of databases, spreadsheets and documents (including PDF and HTML) as well as exportation of text analysis results to common industry file formats (Excel, SPSS, ASCII, HTML, XML, MS Word) and graphs (PNG, BMP and JPEG).