AUTOR:     Diman Ghazi, Diana Inkpen, Stan Szpakowicz
AFILIACJA: University of Ottawa
TYTUŁ:     Prior and contextual emotion of words in sentential context


A set of words labeled with their prior emotion is an obvious place to
start on the automatic discovery of the emotion of a sentence, but it
is clear that context must also be considered. It may be that no
simple function of the labels on the individual words captures the
overall emotion of the sentence; words are interrelated and they
mutually influence their affect-related interpretation. It happens
quite often that a word which invokes emotion appears in a neutral
sentence, or that a sentence with no emotional word carries an
emotion. This could also happen among different emotion classes. The
goal of this work is to distinguish automatically between prior and
contextual emotion, with a focus on exploring features important in
this task. We present a set of features which enable us to take the
contextual emotion of a word and the syntactic structure of the
sentence into account to put sentences into emotion classes. The
evaluation includes assessing the performance of different feature
sets across multiple classification methods.We show the features and a
promising learning method which significantly outperforms two
reasonable baselines. We group our features by the similarity of their
nature. That is why another facet of our evaluation is to consider
each group of the features separately and investigate how well they
contribute to the result. The experiments show that all features
contribute to the result, but it is the combination of all the
features that gives the best performance.