Scopus Indexed Paper

Paper Details


Title
A survey on emotion detection: A lexicon based backtracking approach for detecting emotion from Bengali text
Abstract
Emotion recognition ability has been introduced as a core component of emotional competence. Every emotion has different ways to be expressed such as text, speech, lyrics etc. This paper reflects the current experimental study and their outcomes on emotion detection from different textual data. In case of lexicon-based analysis, the position of emotional lexicons really varies the state of an emotion. In this empirical study, our focus was to find how people use the emotional keywords to express their emotions. We have presented an emotion detection model to extract emotion from Bengali text at the sentence level. In order to detect emotion from Bengali text, we have considered two basic emotion `happiness' and `sadness'. Our proposed model detects emotion on the basis of the sentiment of each sentence associated with it. A lexicon based backtracking approach has been introduced for recognizing the sentiments of sentences to show how frequently people express their emotion in the last part of a sentence. Proposed method can produce a result with 77.16 accuracies.
Keywords
Databases, Genetic expression, Speech, Blogs, Computer science, Emotion recognition, Supervised learning
Authors
Tapasy Rabeya ; Sanjida Ferdous ; Himel Suhita Ali ; Narayan Ranjan Chakraborty
Phone
Journal or Conference Name
20th International Conference of Computer and Information Technology, ICCIT 2017
Publish Year
2018
Indexing
Scopus