Sentiment analysis of electronic word of mouth (E-WoM) on e-learning.

Obot, Okure Udo; Attai, Kingsley Friday; Onwodi, Gregory O.; James, Imaobong; John, Anietie

Abstract

The proliferation of social media and the internet has given people many opportunities to air their views and to be at liberty to say what they feel without hindrance. This is beneficial to commercial organizations and the general well-being of the populace. However, the cost of this freedom is that spamming is practiced with little or no control. This chapter focuses on the electronic word of mouth (eWOM) of opinion holders and the sentiments expressed in eWOM. One of the areas of life impacted by sentiment is electronic learning because it has become a prevalent mode of learning. The study aims to analyze eWOM on e-learning which can help in identifying learners' sentiments. Findings from three thousand tweets show more neutral sentiments, followed by positive sentiments. Suggestions and recommendations as well as the future directions for sentiment analysis of eWOM on e-learning are also discussed in this chapter.

Citation

OBOT, O.U., ATTAI. K.F., ONWODI, G., JAMES, I. and JOHN, A. 2025. Sentiment analysis of electronic word of mouth (E-WoM) on e-learning. In Khosrow-Pour, M. (ed.) Encyclopedia of information science and technology. Sixth edition. Hershey: IGI Global [online], chapter 57. Available from: https://doi.org/10.4018/978-1-6684-7366-5.ch057

• Other Type: Reference Work Contribution
• Acceptance Date: Oct 27, 2023
• Online Publication Date: Jul 1, 2024
• Publication Date: Dec 31, 2025
• Deposit Date: Jan 9, 2024
• Publicly Available Date: Jan 9, 2024
• Publisher: IGI Global
• Edition: Sixth edition
• Chapter Number: 57
• ISBN: 9781668473665
• DOI: https://doi.org/10.4018/978-1-6684-7366-5.ch057
• Keywords: Sentiment analysis; Word-of-mouth; Social media; e-Learning; e-Learning students
• Public URL: https://rgu-repository.worktribe.com/output/2126964
• Contract Date: Sep 22, 2023