ABSTRACT
This chapter describes the research trends in text emotion detection (TED). It explains text emotion detection and its applications, affective computing, sentiment analysis (SA), and multidisciplinary and its existence in TED problems. The chapter also describes the current status of TED through a literature review 2015 and 2016. It also explains some of the challenges facing the research field, including technologies used, the length of the texts, and quality assurance. TED is considered a recent field of research related to SA, which aims to detect positive, neutral, or negative feelings from text. SA or opinion mining (OM) is the computational study of people's opinions, attitudes and emotions toward an entity. Affective computing is an emerging technology and focused on human studies that investigate computer science, cognitive science, psychology, and behaviors of humans. Emotions in humans are complex biological, psychological, social, and cultural processes that must be studied interdisciplinarily. Multidisciplinary can be treated in three different approaches: interdisciplinary, transdisciplinary, and cross-disciplinary.
