Rezvan MohammadiBaghmolaei

Word embedding is known as one of the fundamental tools in natural language processing. Extensive studies have been done to analyze the performance of word embedding models in different sentiment analysis tasks. However, very few works investigated the affective aspects of these models in emotion analysis area which has been growing fast recently. This article overviews and analyzes word embedding specifically for emotion analysis and presents new research directions accordingly. More particularly, after investigating the currently affective and non-affective works on word vectors, a framework for building emotional-aware word vectors is proposed.