..Some time ago I did a word cloud for representing a Google Scholar search result. Tal Galili pointed me at a post by Drew Conway that expanded on the topic of word clouds lacking spatial meaning. In fact the spatial ordering of words in a word cloud is arbitrary and meaningless..

As I am an ecologist, I soon came to the idea that text could be treated as a multivariate data set – assuming that words can be treated as species and sentences being similar to samples. So, presuming that it makes sense to put sentences and words in a cross-table as I similarly would do with a species / samples matrix, it may also be sensible to analyze such a matrix by ordination-methods for multivariate data, mostly used by ecologist recently. I chose NMDS ordination, as it is robust and quite easy to compute with R-package {vegan}.

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