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SPSS Unveils Text Mining Tool

June 17 2008

Research and predictive analytics software giant SPSS has launched a text mining tool to enable users to analyze unstructured data from social media, consumer blogs, community boards, e-mail, call center notes, RSS feeds and surveys.

Powered by the firm's language processing technology, the new SPSS Text Mining software pulls key concepts from this unstructured data and groups them into categories - in eight native languages. Extracted concepts and categories are then combined with structured data to provide insights into actions, behaviors, patterns and associations.

In addition, the new software uses text link analysis to identify and extract sentiments, such as preferences and opinions, from text in multiple languages. By capturing the attitudes and thoughts of individuals, the firm says organizations are able to gain a more complete view of their customers and constituents and build more accurate predictive models.

Olivier Jouve, VP of Corporate Development, says this new service provides the most complete view of the customer through the combined analysis of text, web and survey data. 'While other companies only provide the text component, we provide a full suite of predictive analytics capabilities - statistics, data and text mining, and enterprise feedback management - allowing our customers to draw more reliable conclusions and quickly take more effective action with their data.'

Niels Schillewaert, Managing Partner of online market research organization InSites Consulting (www.insites.eu) which deploys the new SPSS service, comments: 'SPSS allows us to track online buzz and enrich the analysis of open ended questions, which provides us with useful customer information.'

Founded in 1968, SPSS is headquartered in Chicago, Illinois, and is online at www.spss.com . The firm recently debuted the latest version of its Dimensions software, which aims to improve response rates, access to respondents, advanced survey creation and interactive results delivery.

All articles 2006-23 written and edited by Mel Crowther and/or Nick Thomas, 2024- by Nick Thomas, unless otherwise stated.

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