  Understanding the complexity of human language requires an appropriate
analysis of the statistical distribution of words in texts. We consider the
information retrieval problem of detecting and ranking the relevant words of a
text by means of statistical information referring to the "spatial" use of the
words. Shannon's entropy of information is used as a tool for automatic keyword
extraction. By using The Origin of Species by Charles Darwin as a
representative text sample, we show the performance of our detector and compare
it with another proposals in the literature. The random shuffled text receives
special attention as a tool for calibrating the ranking indices.
