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What Makes Us Feel Good? Exploring JMP(R) Text Explorer ( 2019-EU-30MP-081 )

Level: Intermediate
Job Function: Analyst / Scientist / Engineer
Anne Hasted, Senior Consultant, Qi Statistics

As members of European Sensory Network (ESN), we were fortunate to be able to access data from a large multinational survey investigating people's perceptions of well-being both in general and in relation to food and beauty products. We have used this data to compare the results obtained by the ESN, using traditional coding methods for text data with those using JMP Text Explorer. This talk shows the advantage of using the features available in JMP Text Explorer to clean and order the data, both in terms of speed and objectivity and easy access to all the statistical mapping techniques in the software. In fairness we also show the disadvantages of a text mining approach due to sparse data. Additionally, we discuss how the advanced analysis features in JMP (SVD and association analysis) helped us to compare attitudes in different cultures.