Vidya M
ABSTRACT
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.
- Dang, N. C., Moreno-García, M. N., & De la Prieta, F. (2020). Sentiment analysis based on deep learning: A comparative study. Electronics, 9(3), 483.Google Scholar
- Agarwal, B., Mittal, N., Agarwal, B., & Mittal, N. (2016). Machine learning approach for sentiment analysis. Prominent feature extraction for sentiment analysis, 21-45.Google ScholarCross Ref
- Baid, P., Gupta, A., & Chaplot, N. (2017). Sentiment analysis of movie reviews using machine learning techniques. International Journal of Computer Applications, 179(7), 45-49.Google Scholar
- Jain, P. K., Pamula, R., & Srivastava, G. (2021). A systematic literature review on machine learning applications for consumer sentiment analysis using online reviews. Computer science review, 41, 100413.Google Scholar
- Singh, J., Singh, G., & Singh, R. (2017). Optimization of sentiment analysis using machine learning classifiers. Human-centric Computing and information Sciences, 7, 1-12.Google Scholar
- Kumar, S., Gahalawat, M., Roy, P. P., Dogra, D. P., & Kim, B. G. (2020). Exploring impact of age and gender on sentiment analysis using machine learning. Electronics, 9(2), 374.Google Scholar
Recommendations
Analysis of quantitative and qualitative indicators of SEE countries scientific output
This paper provides a comprehensive comparative analysis of the South East European countries scientific output and impact by Frascati fields of science in the period of 2005---2010. The aim is to determine the volume of scientific output in the ...
Qualitative and quantitative analyses of anatomists' research: evaluation of multidisciplinarity and trends in scientific production
Our aim was to evaluate the impact of anatomy as a multidisciplinary area and to identify trends in research by anatomists over time. Data from three main sources were analyzed: SCImago Journal & Country Rank (SJR), using the number of total documents ...
Big data analytics and machine learning: A retrospective overview and bibliometric analysis
Highlights- A bibliometric study of big data analytics and machine learning.
- A sample of ...
AbstractThe research and practice of information systems have progressed by leaps and bounds due to the emergence of big data analytics and machine learning. The paper undertakes a bibliometric study to analyze the contributions of major ...
Comments