Twitter Data Classification using Hidden Markov Model - Zaman, Dr Kazi Arif-Uz (International Journal of Advanced Science and Technology, 2020)
Twitter data generally contains any reviews, feedbacks and sentiments of the customers regarding the product or service. However, customers are often confused and overwhelmed by the raw data that has been generated in the twitter. A promising solution is to analyze the texts and the labels (or, positive and negative review of the customers) of the twitter data using text classifier. In this paper, text classifier constructed using Hidden Markov model is utilized. The effectiveness of the classifier is demonstrated using the twitter review of a product. On the case example, it was observed that the proposed model performed well in terms of classification accuracy and F-measure. The outcomes of this study can be used to develop more sophisticated statistical models as well as to compare other text classifiers from other twitter text data.