  In this article, we present the first in depth linguistic study of human
feelings. While there has been substantial research on incorporating some
affective categories into linguistic analysis (e.g. sentiment, and to a lesser
extent, emotion), the more diverse category of human feelings has thus far not
been investigated. We surveyed the extensive interdisciplinary literature
around feelings to construct a working definition of what constitutes a feeling
and propose 9 broad categories of feeling. We identified potential feeling
words based on their pointwise mutual information with morphological variants
of the word `feel' in the Google n-gram corpus, and present a manual annotation
exercise where 317 WordNet senses of one hundred of these words were
categorised as `not a feeling' or as one of the 9 proposed categories of
feeling. We then proceeded to annotate 11386 WordNet senses of all these words
to create WordNet-feelings, a new affective dataset that identifies 3664 word
senses as feelings, and associates each of these with one of the 9 categories
of feeling. WordNet-feelings can be used in conjunction with other datasets
such as SentiWordNet that annotate word senses with complementary affective
properties such as valence and intensity.
