Compositionality Principle in Recognition of Fine-Grained Emotions from Text

Abstract

The recognition of personal emotional state or sentiment conveyed through text is the main task we address in our research. The communication of emotions through text messaging and posts of personal blogs poses the 'informal style of writing' challenge for researchers expecting grammatically correct input. Our Affect Analysis Model was designed to handle the informal messages written in an abbreviated or expressive manner. While constructing our rule-based approach to affect recognition from text, we followed the compositionality principle. Our method is capable of processing sentences of different complexity, including simple, compound, complex (with complement and relative clauses), and complex-compound sentences. The evaluation of the Affect Analysis Model algorithm showed promising results regarding its capability to accurately recognize affective information in text from an existing corpus of personal blog posts.