Sentimental Analysis on Online Education Using Machine Learning Models
- Title
- Sentimental Analysis on Online Education Using Machine Learning Models
- Creator
- Mathew S.T.; Jacob L.
- Description
- Sentimental analysis is a simple natural language processing technique for classifying and identifying the sentiments and views represented in a source text. Corona pandemic has shifted the focus of education from traditional classrooms to online classes. Students mental and psychological states alter as a result of this transition. Sentimental study of the opinions of online education students can aid in understanding the students learning conditions. During the corona pandemic, only, students enrolled in online classes were surveyed. Only, students who are in college for pre-graduation, graduation, or post-graduation were used in this study. To grasp the pupils feelings, machine learning models were developed. Using the dataset, we were able to identify and visualize the students feelings. Students favorable, negative, and neutral opinions can be successfully classified using machine learning algorithms. The Naive Bayes method is the most accurate method identified. Logistic regression, support vector machine, decision tree, and random forest these algorithms also gave comparatively good accuracy. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
- Source
- Lecture Notes in Networks and Systems, Vol-462, pp. 413-422.
- Date
- 2022-01-01
- Publisher
- Springer Science and Business Media Deutschland GmbH
- Subject
- Emotion classification; Machine learning; Natural language processing (NLP); Online education; Sentimental analysis
- Coverage
- Mathew S.T., Department of Data Science, Christ University, Bengaluru, India; Jacob L., Department of Data Science, Christ University, Bengaluru, India
- Rights
- Restricted Access
- Relation
- ISSN: 23673370; ISBN: 978-981192210-7
- Format
- Online
- Language
- English
- Type
- Conference paper
Collection
Citation
Mathew S.T.; Jacob L., “Sentimental Analysis on Online Education Using Machine Learning Models,” CHRIST (Deemed To Be University) Institutional Repository, accessed February 26, 2025, https://archives.christuniversity.in/items/show/20329.