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Title : COLLABORATIVE MULTI-DOMAIN SENTIMENT CLASSIFICATION APPROACH FOR SOCIAL MEDIA
Author : SREEKANTAM VASUDHA, DIGALA RAGHAVA RAJU, K BALAJI SUNIL CHANDRA
Our strategy is based on the central principle of sentiment analysis, which is the study of human health as it relates to social media. It is well-known that current sentiment categorization is an issue that is very domain-dependent. So, it accurately predicts a person's depression rate but offers an extremely low estimate. Using a collaborative multi domain sentiment classifier, which has the benefit of more precisely determining a person's depressive condition, may fix the issue. Our goal is to use multi-task learning as a collaborative framework to train sentiment classifiers for various domains. Its many applications include marketing research, political campaigns, brand messaging, and consumer feedback gathering. Throughout the subject review The Bag of Words (BODW) approach is crucial. The most crucial words in a paper could stand for an opinion or a fact about the subject. Both the fact and the feeling stand for the objective and subjective labels, respectively. Fr
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