Abstract
Research on social media has to date assumed
that all posts from an account are authored by
the same person. In this study, we challenge
this assumption and study the linguistic differences between posts signed by the account
owner or attributed to their staff. We introduce
a novel data set of tweets posted by U.S. politicians who self-reported their tweets using a
signature. We analyze the linguistic topics and
style features that distinguish the two types
of tweets. Predictive results show that we are
able to distinguish between owner and staff attributed tweets with good accuracy, even when
not using any training data from that account