Exploiting a bootstrapping approach for automatic annotation of emotions in texts

The objective of this research is to develop a technique to automatically annotate emotional corpora. The complexity of automatic annotation of emotional corpora still presents numerous challenges and thus there is a need to develop a technique that allow us to tackle the annotation task. The relevance of this research is demonstrated by the fact that people's emotions and the patterns of these emotions provide a great value for business, individuals, society or politics. Hence, the creation of a robust emotion detection system becomes crucial. Due to the subjectivity of the emotions, the main challenge for the creation of emotional resources is the annotation process. Thus, with this staring point in mind, the objective of our paper is to illustrate an innovative and effective bootstrapping process for automatic annotations of emotional corpora. The evaluations carried out confirm the soundness of the proposed approach and allow us to consider the bootstrapping process as an appropriate approach to create resources such as an emotional corpus that can be employed on supervised machine learning towards the improvement of emotion detection systems.