Qualitative Analysis on Machine Learning Through Biblioshiny

Machine learning augments business firms by enhancing their business operations and by reduction in costs. It assists business houses to visualize the historical patterns and to envisage future decisions. Machine learning applies algorithms and models to assess the data patterns. Sentiment analysis is a form of Natural Language Processing for regulating the feedback from different ends. The study analysed 620 global publications pertaining to Machine learning and sentiment analysis indexed in Scopus database. The article demonstrated a Three field plot portrays the relationship between authors, countries, and keywords; authors' influence on sources; word counts and word growth; and a collaborative network of papers. The widely held articles of Machine Learning and Sentiment Analysis is published as journal articles, and the number of publications is continuously increasing. In a ranking most productive nations, India came out with the highest citations (1054), followed by USA (504), and Chine (354). The productive authors in the field of Machine Learning and Sentiment Analysis were Wang X has contributed 5 articles followed by Li Z, Wang Y, Yaqub U, with 4 articles. The Journal Information Processing and Management had 24 Publications around the world and also has the total citations of 763 followed by Artificial Intelligence Review (475 Citations). University of Florida was the contributing majority of 21 articles followed by The Hongkong Polytechnic University with 16 articles.