  Social media texts differ from regular texts in various aspects. One of the
main differences is the common use of informal name variants instead of
well-formed named entities in social media compared to regular texts. These
name variants may come in the form of abbreviations, nicknames, contractions,
and hypocoristic uses, in addition to names distorted due to capitalization and
writing errors. In this paper, we present an analysis of the named entities in
a publicly-available tweet dataset in Turkish with respect to their being name
variants belonging to different categories. We also provide finer-grained
annotations of the named entities as well-formed names and different categories
of name variants, where these annotations are made publicly-available. The
analysis presented and the accompanying annotations will contribute to related
research on the treatment of named entities in social media.
