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A survey on emotion detection: A lexicon based backtracking approach for detecting emotion from Bengali text

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dc.contributor.author Rabeya, Tapasy
dc.contributor.author Ferdous, Sanjida
dc.contributor.author Ali, Himel Suhita
dc.contributor.author Chakraborty, Narayan Ranjan
dc.date.accessioned 2019-05-16T07:16:06Z
dc.date.available 2019-05-16T07:16:06Z
dc.date.issued 2018-02-08
dc.identifier.isbn 978-1-5386-1151-7
dc.identifier.uri http://hdl.handle.net/123456789/70
dc.description.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. en_US
dc.language.iso en_US en_US
dc.publisher IEEE en_US
dc.subject Databases en_US
dc.subject Genetic expression en_US
dc.subject Speech en_US
dc.subject Blogs en_US
dc.subject Computer science en_US
dc.subject Emotion recognition en_US
dc.subject Supervised learning en_US
dc.title A survey on emotion detection: A lexicon based backtracking approach for detecting emotion from Bengali text en_US
dc.type Other en_US


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