  In this paper, we introduce the first and largest Hindi text corpus, named
BHAAV, which means emotions in Hindi, for analyzing emotions that a writer
expresses through his characters in a story, as perceived by a narrator/reader.
The corpus consists of 20,304 sentences collected from 230 different short
stories spanning across 18 genres such as Inspirational and Mystery. Each
sentence has been annotated into one of the five emotion categories - anger,
joy, suspense, sad, and neutral, by three native Hindi speakers with at least
ten years of formal education in Hindi. We also discuss challenges in the
annotation of low resource languages such as Hindi, and discuss the scope of
the proposed corpus along with its possible uses. We also provide a detailed
analysis of the dataset and train strong baseline classifiers reporting their
performances.
