  Several lexica for sentiment analysis have been developed and made available
in the NLP community. While most of these come with word polarity annotations
(e.g. positive/negative), attempts at building lexica for finer-grained emotion
analysis (e.g. happiness, sadness) have recently attracted significant
attention. Such lexica are often exploited as a building block in the process
of developing learning models for which emotion recognition is needed, and/or
used as baselines to which compare the performance of the models. In this work,
we contribute two new resources to the community: a) an extension of an
existing and widely used emotion lexicon for English; and b) a novel version of
the lexicon targeting Italian. Furthermore, we show how simple techniques can
be used, both in supervised and unsupervised experimental settings, to boost
performances on datasets and tasks of varying degree of domain-specificity.
