A comparative recapitulating study of recent sentiment analysis approaches

In accordance with the convention, sentiments are defined as a thought, judgement or attitude prompted by feelings or a specific notion. With explosion of social networks, every individual/user actively manifests and share their ideas or emotions in disparate life aspects. Past few years have shown Sentiment Analysis as a pivotal activity in various systems and thus become a center of attention for the researchers. Considerable amount of research has already been done to inspect and examine user's sentiments, which are extracted either from web pages or social media, through lexicon, machine learning or deep learning techniques. This paper presents a vital contribution in this field of research through comprehensive exploration of most recent articles/studies, extremely aiming to highlight the applicability of sentiment analysis in software engineering field as well as through bio-inspired algorithms along with other modi operandi, and thereby helping practitioners to get detailed insights of some of the lately exercised feature extraction tactics, methodologies and datasets considered for the analysis of sentiment-specific studies.