  In this paper we quantify the consistency of word usage in written texts
represented by complex networks, where words were taken as nodes, by measuring
the degree of preservation of the node neighborhood.} Words were considered
highly consistent if the authors used them with the same neighborhood. When
ranked according to the consistency of use, the words obeyed a log-normal
distribution, in contrast to the Zipf's law that applies to the frequency of
use. Consistency correlated positively with the familiarity and frequency of
use, and negatively with ambiguity and age of acquisition. An inspection of
some highly consistent words confirmed that they are used in very limited
semantic contexts. A comparison of consistency indices for 8 authors indicated
that these indices may be employed for author recognition. Indeed, as expected
authors of novels could be distinguished from those who wrote scientific texts.
Our analysis demonstrated the suitability of the consistency indices, which can
now be applied in other tasks, such as emotion recognition.
