Enigmas in Emotion Detection Techniques Tools: Challenges and Concerns

Emotion detection is a branch of sentiment analysis that focuses on the identification and study of emotions. Text mining, analysis of extracted information, and in-depth research are now at the centre of organisational success due to the development of web 2.0. It enables service providers to provide their clients with specialized services. Due to the simplicity of obtaining data and the enormous advantages its deliverables give, text-based extraction and analysis are now the topics of much research. The notion of ED from texts is examined in this article, which also highlights the major techniques that academics have taken to develop ED systems that employ texts. The proposals' key contributions, methods used, datasets consulted, outcomes attained, and strengths and limitations are described. Additionally, emotion-labelled data sources are offered to give beginners access to appropriate text datasets for ED. The essay concludes by outlining several unresolved problems and potential lines of inquiry for text-based ED. Due to its numerous potentials uses in business, cultural studies, cognitive science, human-computer interaction, cognitive computing, etc., emotion recognition in the text has recently gained popularity. The availability of a wealth of textual material, particularly opinionated and self-expressive writing, also considerably increased public awareness of this issue.