  The use of statistical methods to analyze large databases of text has been
useful to unveil patterns of human behavior and establish historical links
between cultures and languages. In this study, we identify literary movements
by treating books published from 1590 to 1922 as complex networks, whose
metrics were analyzed with multivariate techniques to generate six clusters of
books. The latter correspond to time periods coinciding with relevant literary
movements over the last 5 centuries. The most important factor contributing to
the distinction between different literary styles was {the average shortest
path length (particularly, the asymmetry of the distribution)}. Furthermore,
over time there has been a trend toward larger average shortest path lengths,
which is correlated with increased syntactic complexity, and a more uniform use
of the words reflected in a smaller power-law coefficient for the distribution
of word frequency. Changes in literary style were also found to be driven by
opposition to earlier writing styles, as revealed by the analysis performed
with geometrical concepts. The approaches adopted here are generic and may be
extended to analyze a number of features of languages and cultures.
