Supervised Machine Learning Techniques for Sentiment Analysis and its Application in Image Processing and Remote Sensing

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Iman M, Subhashish Tiwari, Swetha Vura, Ajay Sudhir Bale, Bharath G, Sharanabasaveshwara H B


As we see the growing social media transparency, where users want to express their opinions we also see a growing need of Sentiment analysis (SA) or Opinion mining. Sentiment Analysis is a process used to interpret user sentiments related to a specific topic. It is a field of study which is formed at the junction of Natural Language Processing (NLP), Machine learning (ML) and Information retrieval (IR). In this paper we will see various types of machine learning (ML) techniques that come under supervised learning. We will be discussing 3 techniques under the domain of Supervised ML, namely,  SVM, Naive Bayes and Maximum Entropy, which are studied and established to be the most accurate. We will see how supervised ML techniques can be applied in Image processing and Remote sensing as well.

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