Sindhi Text-Based Students Sentiment Analysis Using Convolutional Neural Network
DOI:
https://doi.org/10.21015/vtcs.v12i2.1943Abstract
Current generation especially the teenager students are using Social Media (SM) platforms at an extreme level even the sentimental angles are too discussed there. In the province Sindh, students mostly prefer to text the message in origin of their mother tongue i.e. Sindhi lexicon for sharing their views regarded politics, religions, sports, education etc.All these sentimental conveys are important for enhancing the academic capabilities.In this research paper, approach is broken down into multiple phases comprising of number of WhatsApp chat, lexicon generation, dataset tokenization, Convolutional Neural Network (CNN); all based on respective sentiments.To validate the experimentation process at standard level. 100 WhatsApp data chats were collected from different levels of students and divided into four categories.The CNN Model is used for sentimental classification. Accuracy, Precision, Recall and F-Score are the four parameters used for model evaluation. The model provides 0.874% accuracy, 0.883% recall, 0.863% precision and 0.745% F-Score.
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