Social Emotion Cause Extraction from Online Texts

Social emotion refers to the emotion evoked to the reader by a textual document. Compared to classical sentiment analysis conducted from the author’s perspective, emotion analysis from the reader’s perspective (i.e. social emotion mining) is an important task in web-based social media analytics, and particularly meaningful for security related applications. Mining the causes of social emotions, i.e. Social Emotion Cause Extraction (SECE), is a new challenging task in social emotion mining, which can help better explain the elicited social emotions in text. In this paper, we propose the SECE task for the first time, and construct a new SECE dataset to support our study. We develop the first computational method for this new task, and conduct experimental studies to evaluate the effectiveness of our proposed method based on the dataset we construct.