Sentiment Forecasting Method on Approach of Supervised Learning by News Comments
Farhana Akter, Shakib Ahamed Tushar, Shameem Alam Shawan, Mumenunnessa Keya, Sharun Akter Khushbu, Sanzidul Isalm · 2021
Sentiment analysis is a process for mining opinion from a text. A lot of work has been done on this field for English language but the numbers don't rise high for the Bengali language. Though Bengali is the seven largest spoken language but a few works have been done for Bengali language all because of the lack of a perfect model and dataset. Everyday not only in our country but also around the world a lot of incidents happen. Because we are currently living in a global community where the news can impact a person's mind beyond borderline of countries. For this aspect it's a great opportunity to analyze the sentiment of the news. To train the model we classified the emotions into three classes. We have tried to classify a person's emotions into three different classes (happy, sad, neutral) for news published on the internet by online newspapers. For Deep learning Recurrent neural network was applied and for Machine learning, we used methods like Multinomial naive Bayes, K-nearest neighbor, Random Forest Classifier, Decision tree classifier, Support vector machine, Logistic Regression to train our model. Among those RNN obtain 95% accuracy.