Abstract
School closures due to the Covid-19 pandemic have changed education forever and we have witnessed the rise of online learning platforms. The education units of the countries made great efforts to adapt to this new order. The expanding, quick spread of the virus and careful steps have prompted the quest for reasonable choices for continuing education to guarantee students get appropriate education and are not impacted logically or mentally. Different methods were attempted to understand how students were affected by this big change. In addition to the significance of traditional surveys and consulting services, the utilization of social media analysis is used as a supportive approach. This paper analyzes the feedback of students on social media via tweets. Deep sentiment analysis is employed to identify embedded emotions such as negative, neutral, and positive. We also aimed to classify irrelevant tweets as the fourth category. Our experiments showed that the tweets are mostly biased toward negative emotions.
Original language | English |
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Title of host publication | Proceedings - 2022 Innovations in Intelligent Systems and Applications Conference, ASYU 2022 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
ISBN (Electronic) | 9781665488945 |
DOIs | |
Publication status | Published - 2022 |
Externally published | Yes |
Event | 2022 Innovations in Intelligent Systems and Applications Conference, ASYU 2022 - Antalya, Turkey Duration: 7 Sept 2022 → 9 Sept 2022 |
Publication series
Name | Proceedings - 2022 Innovations in Intelligent Systems and Applications Conference, ASYU 2022 |
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Conference
Conference | 2022 Innovations in Intelligent Systems and Applications Conference, ASYU 2022 |
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Country/Territory | Turkey |
City | Antalya |
Period | 7/09/22 → 9/09/22 |
Bibliographical note
Publisher Copyright:© 2022 IEEE.
Keywords
- COVID-19
- Deep Learning
- Education
- LSTM
- Sentiment Analysis
- Social Media