Sentiment analysis of micro-blogging sites using supervised learning: a narrative review of recent studies Online publication date: Thu, 07-Apr-2022
by Akanksha Bisht; H.S. Bhadauria; Jitendra Virmani; Annapurna Singh; Kriti
International Journal of Knowledge and Learning (IJKL), Vol. 15, No. 2, 2022
Abstract: Sentiment analysis is a task of predicting sentiments from the opinionated data and classifies them as positive, negative, ratings (stars or numerical), thumbs up - thumbs down and so forth. In the present survey, we have covered numerous datasets, methodologies, developments together with indications for advances in the near future. Inspired by the achievements of deep learning, plenty of researchers are utilising the deep learning models for conducting sentiment analysis. Therefore, we have highlighted some studies regarding the use of machine learning and deep learning models on different micro-blogging sites with the evolution in sentiment analysis. The survey presents a number of suitable illustrations-most prominently, a table that summarises previous papers along different dimensions such as types of objectives, classification techniques and dataset used.
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