Publications by authors named "H Berkers"

Background: Empirical evidence for effective patient-researcher collaboration in basic research is lacking. This study aims to explore good working models and impact of patient involvement in basic rheumatology research and to identify barriers and facilitators.

Method: A responsive evaluation of a three years' participatory research project in a basic and translational laboratory research setting.

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Organizations are increasingly interested in classifying texts or parts thereof into categories, as this enables more effective use of their information. Manual procedures for text classification work well for up to a few hundred documents. However, when the number of documents is larger, manual procedures become laborious, time-consuming, and potentially unreliable.

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Despite the ubiquity of textual data, so far few researchers have applied text mining to answer organizational research questions. Text mining, which essentially entails a quantitative approach to the analysis of (usually) voluminous textual data, helps accelerate knowledge discovery by radically increasing the amount data that can be analyzed. This article aims to acquaint organizational researchers with the fundamental logic underpinning text mining, the analytical stages involved, and contemporary techniques that may be used to achieve different types of objectives.

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