  The problem of fake news has gained a lot of attention as it is claimed to
have had a significant impact on 2016 US Presidential Elections. Fake news is
not a new problem and its spread in social networks is well-studied. Often an
underlying assumption in fake news discussion is that it is written to look
like real news, fooling the reader who does not check for reliability of the
sources or the arguments in its content. Through a unique study of three data
sets and features that capture the style and the language of articles, we show
that this assumption is not true. Fake news in most cases is more similar to
satire than to real news, leading us to conclude that persuasion in fake news
is achieved through heuristics rather than the strength of arguments. We show
overall title structure and the use of proper nouns in titles are very
significant in differentiating fake from real. This leads us to conclude that
fake news is targeted for audiences who are not likely to read beyond titles
and is aimed at creating mental associations between entities and claims.
