The workflow clusters Grimm’s tales corpus. We start by preprocessing the data and constructing the bag of words matrix. Then we compute cosine distances between documents and use Hierarchical Clustering, which displays the dendrogram. We observe how well the type of the tale corresponds to the cluster in the MDS.
Text mining requires careful preprocessing. Here’s a workflow that uses simple preprocessing for creating tokens from documents. First, it applies lowercase, then splits text into words, and finally, it removes frequent stopwords. Preprocessing is language specific, so change the language to the language of texts where required. Results of preprocessing can be observe in a Word Cloud.