“…The work by Wang et al, [65] proposed a social media analytics engine that employs a fuzzy similarity-based classification method to automatically classify text messages into sentiment categories (positive, negative, neutral and mixed), with the ability to identify their prevailing emotion categories (e.g., satisfaction, happiness, excitement, anger, sadness, and anxiety). Others attempted to identify the semantic similarity of very short texts in Twitter and Facebook [66]. Also, a lexical similarity-based approach for extracting subjectivity in documents extracted from social media was proposed in [67].…”