See how to combine text analysis with predictive modeling to derive sentiments from opinions or product choices to help understand the underlying emotions related to survey responses.
Presenter: Mike Anderson
Mastering JMP®
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Deriving Sentiments from Opinions or Product Choices
Using JMP Pro to Derive Sentiments from Opinions or Product Choices
See how to:
- Define basic text mining components: corpus (data table), document (row), Document Term Matrix (occurrences of terms of interest in corpus)
- Curate data using distribution, recode, stemming and Word Cloud to prepare for modeling
- Model the data using Fit Model, Generalized Regression, Elastic Net and BIC model validation
- Examine statistics, Solution Path and active parameters to evaluate model
Resources
- Journal and files
- JMP Discovery Summit 2017 presentation
- JMP Discovery Summit 2018 presentation on Modeling Consumer Feedback With Text Mining Features in JMP® Pro
- Toronto Casino Survey Data
- Using Text Explorer to Extend Analysis (Mastering JMP video)