The text data must first be prepared for these analyses. See the Text Explorer – Describing Unstructured Text Data guide and the JMP Help for information on using the Text Explorer platform to do this.
Analyzing Unstructured Text
Text analysis involves transforming prepared text data into a Document Term Matrix (DTM). Each row in the DTM corresponds to a document (a cell in the column of text data), and each column in the DTM corresponds to a term. The DTM is then used as an input in all analyses.
Here we selected Save Document Term Matrix under the Red Triangle and used the default specifications. A number of analysis options are available from the top red triangle menu in the text explorer analysis report:
- Latent Class Analysis groups documents into clusters of similar documents.
- Latent Semantic Analysis, SVD is a dimension reduction technique similar to principal components analysis.
- Topic Analysis groups words into themes or topics, and is similar to factor analysis.
- Cluster Terms or Cluster Documents performs hierarchical clustering of the terms or documents.
Here we selected Latent Semantic Analysis, SVD using the default settings. Then selected SVD Scatter Plot Matrix.
Saving Results
Text Explorer analysis results, such as the DTM, can be saved to the data table. The resulting columns can then be used as predictors in other analyses.
- To save information that corresponds to documents, save the Document Term Matrix, Document Singular Vectors or Document Topic Vectors.
- To save information that corresponds to terms, without respect to the specific documents, save the Term Table, Term Singular Vectors or Term Topic Vectors.
Visit Basic Analysis > Text Explorer in JMP Help to learn more.