Examining Emotional Reactions to the COVID-19 Crisis Through Twitter Data Analysis: A Comparative Study of Classification Techniques
COVID-19 has significantly impacted peoples’ mental health because of isolation and social distancing measures. It practically impacts every segment of people’s daily lives and causes a medical problem that spreads throughout the entire world. This pandemic has caused an increased emotional distress...
Saved in:
| Main Authors: | Saira Yaqub, Muhammad Shoaib, Abdul Jaleel, Syed Khaldoon Khurshid, Shazia Arshad, Riaz Ahmad Ziar |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2024-01-01
|
| Series: | Applied Computational Intelligence and Soft Computing |
| Online Access: | http://dx.doi.org/10.1155/2024/8889330 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Exploring Sign Language Detection on Smartphones: A Systematic Review of Machine and Deep Learning Approaches
by: Iftikhar Alam, et al.
Published: (2024-01-01) -
EmoNet: Deep Attentional Recurrent CNN for X (Formerly Twitter) Emotion Classification
by: Md. Shakil Hossain, et al.
Published: (2025-01-01) -
Emotional reactions towards vaccination during the emergence of the Omicron variant: Insights from twitter analysis in South Africa
by: Blessing Ogbuokiri, et al.
Published: (2025-06-01) -
Characterizing the Reaction of Doctors to COVID-19 on Twitter
by: Katie Hsia, et al.
Published: (2022-04-01) -
Tourism content on Twitter (X) during a crisis
by: Lluís Alfons Garay-Tamajón, et al.
Published: (2024-11-01)