Bootstrapping technique + embeddings = emotional corpus annotated automatically

Detecting depression or personality traits, tutoring and student behaviour systems, or identifying cases of cyber-bulling are a few of the wide range of the applications, in which the automatic detection of emotion is crucial. This task can contribute to the benefit of business, society, politics or education. The main objective of our research is focused on the improvement of the supervised emotion detection systems developed so far, through the definition and implementation of a technique to annotate large scale English emotional corpora automatically and with high standards of reliability. Our proposal is based on a bootstrapping process made up two main steps: the creation of the seed using NRC Emotion Lexicon and its extension employing the distributional semantic similarity through words embeddings. The results obtained are promising and allow us to confirm the soundness of the bootstrapping technique combined with the word embedding to label emotional corpora automatically.