Performance Analysis of Various Machine Learning Classification Models Using Twitter Data: National Education Policy
- Title
- Performance Analysis of Various Machine Learning Classification Models Using Twitter Data: National Education Policy
- Creator
- Agarwal K.; Deepa S.; Sivabalan R.V.; Balakrishnan C.
- Description
- With the exponential growth of social networking sites, people are using these platforms to express their sentiments on everyday issues. Collection and analysis of people's reactions to purchases of products, public services, etc. are important from a marketing and innovation perspective. Sentiment analysis also called opinion mining or emotion extraction is the classification of emotions in text. This technique has been widely used over the years to determine sentiment within given text data. Twitter is a social media platform primarily used by people to express their feelings about specific events. In this paper, collected tweets about National Education Policy which has been a hot topic for a while; and analyzed them using various machine learning algorithms such as Random Forest classifier, Logistic Regression, SVM, Decision Tree, XGBoost, Naive Bayes. This study shows that the Decision tree algorithm is performing best, compare to all the other algorithms. 2023 IEEE.
- Source
- Proceedings of the International Conference on Intelligent and Innovative Technologies in Computing, Electrical and Electronics, ICIITCEE 2023, pp. 862-870.
- Date
- 2023-01-01
- Publisher
- Institute of Electrical and Electronics Engineers Inc.
- Subject
- classifier; Decision Tree; Gaussian Naive Bayes; Logistic Regression; Machine Learning; Natural Language Processing; Random Forest; Sentiment Analysis; Support Vector Machines; Twitter; XGBoost
- Coverage
- Agarwal K., Christ University, Department Computer Science, Bangalore, India; Deepa S., Christ University, Department Computer Science, Bangalore, India; Sivabalan R.V., Christ University, Department Computer Science, Bangalore, India; Balakrishnan C., Christ University, Department Computer Science, Bangalore, India
- Rights
- Restricted Access
- Relation
- ISBN: 978-166546263-1
- Format
- Online
- Language
- English
- Type
- Conference paper
Collection
Citation
Agarwal K.; Deepa S.; Sivabalan R.V.; Balakrishnan C., “Performance Analysis of Various Machine Learning Classification Models Using Twitter Data: National Education Policy,” CHRIST (Deemed To Be University) Institutional Repository, accessed February 24, 2025, https://archives.christuniversity.in/items/show/19964.