Sentiment analysis and emotion detection of post-COVID educational Tweets: Jordan case.
Soc Netw Anal Min
; 13(1): 39, 2023.
Article
in English
| MEDLINE | ID: covidwho-2277179
ABSTRACT
Education evolved dramatically under Covid-19, and owing to the conditions, distant learning became mandatory. However, this has opened new realities to the educational business under the label of "Hybrid-Learning," where educational institutions are still using online learning in addition to face-to-face learning, which has changed people's lives and split their opinions and emotions. As a result, this study investigated the Jordanian community's perspectives and feelings on the transition from pure face-to-face education to blended education by examining related tweets in the post-COVID era. Specifically, using NLP Emotion detection and Sentiment Analysis approaches, as well as deep learning models. As a result of analyzing the collected tweets, 18.75% of studied Jordanian's community sample are dissatisfied (Anger and Hate), 21.25% are negative (Sad), 13% are Happy, and 24.50 percent are Neutral about it.
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Type of study:
Diagnostic study
Topics:
Long Covid
Language:
English
Journal:
Soc Netw Anal Min
Year:
2023
Document Type:
Article
Affiliation country:
S13278-023-01041-8
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