Deep Learning and Machine Learning-Based Model for Conversational Sentiment Classification

Urdu Sentiment Analysis Sadness
DOI: 10.32604/cmc.2022.025543 Publication Date: 2022-03-29T06:13:38Z
ABSTRACT
In the current era of internet, people use online media for conversation, discussion, chatting, and other similar purposes. Analysis such material where more than one person is involved has a spate challenge as compared to text analysis tasks. There are several approaches identify users’ emotions from conversational English language, however regional or low resource languages have been neglected. The Urdu language them despite being used by millions users across globe, with best our knowledge there exists no work on dialogue in language. Therefore, this paper, we proposed model which utilizes deep learning machine classification text. To accomplish task, first created dataset help existing datasets analysis. After that, preprocessed data selected dialogues common emotions. Once prepared, different techniques emotion. We tuned algorithms according datasets. experimental evaluation shown encouraging results 67% accuracy datasets, 10, 000 classified into five i.e., joy, fear, anger, sadness, neutral. believe that effort emotion detection domain.
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