  Several studies have used Wikipedia (WP) data-set to analyse worldwide human
preferences by languages. However, those studies could suffer from bias related
to exceptional social circumstances. Any massive event promoting the
exceptional edition of WP can be defined as a source of bias. In this article,
we follow a procedure for detecting outliers. Our study is based on $12$
languages and $13$ different categories. Our methodology defines a parameter,
which is language-depending instead of being externally fixed. We also study
the presence of human cyclic behaviour to evaluate apparent outliers. After our
analysis, we found that the outliers in our data set do not significantly
affect using the whole Wikipedia-data set as a digital footprint to analyse
worldwide human preferences.
