  The presence of gender stereotypes in many aspects of society is a well-known
phenomenon. In this paper, we focus on studying and quantifying such
stereotypes and bias in the Man Bookers Prize winning fiction. We consider 275
books shortlisted for Man Bookers Prize between 1969 and 2017. The gender bias
is analyzed by semantic modeling of book descriptions on Goodreads. This
reveals the pervasiveness of gender bias and stereotype in the books on
different features like occupation, introductions and actions associated to the
characters in the book.
