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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Effect of daily new cases of COVID-19 on public sentiment and concern: Deep learning-based sentiment classification and semantic network analysis
ShaoPeng Che, Xiaoke Wang, Shunan Zhang, et al.
Journal of Public Health (2023) Vol. 32, Iss. 3, pp. 509-528
Open Access | Times Cited: 11

Showing 11 citing articles:

Social media sentiment analysis and opinion mining in public security: Taxonomy, trend analysis, issues and future directions
Mohd Suhairi Md Suhaimin, Mohd Hanafi Ahmad Hijazi, Ervin Gubin Moung, et al.
Journal of King Saud University - Computer and Information Sciences (2023) Vol. 35, Iss. 9, pp. 101776-101776
Open Access | Times Cited: 21
Local government social media use, citizen satisfaction, and citizen compliance: Evidence from the COVID-19 outbreak in Shanghai
Qiang Chen, Yangyi Zhang, Richard Evans
International Journal of Disaster Risk Reduction (2024) Vol. 101, pp. 104238-104238
Closed Access | Times Cited: 6
Comprehensive review and comparative analysis of transformer models in sentiment analysis
Hadis Bashiri, Hassan Naderi
Knowledge and Information Systems (2024)
Closed Access | Times Cited: 5
Comparative Analysis of Classification Methods in Sentiment Analysis: The Impact of Feature Selection and Ensemble Techniques Optimization
Sarjon Defit, Agus Perdana Windarto, Putrama Alkhairi
Telematika (2024) Vol. 17, Iss. 1, pp. 52-67
Open Access | Times Cited: 2
Are the epidemic prevention facilities effective? How cities should choose epidemic prevention facilities: Taking Wuhan as an example
Lei Hua, Rong Ran, Zhengxing Ni
Frontiers in Public Health (2023) Vol. 11
Open Access | Times Cited: 5
Shifting sentiments: analyzing public reaction to COVID-19 containment policies in Wuhan and Shanghai through Weibo data
Zhihang Liu, Jinlin Wu, Connor Y. H. Wu, et al.
Humanities and Social Sciences Communications (2024) Vol. 11, Iss. 1
Open Access | Times Cited: 1
ChatGPT: unlocking the potential of Artifical Intelligence in COVID-19 monitoring and prediction
Alberto Giovanni Gerli, Joan B. Soriano, Gianfranco Alicandro, et al.
Panminerva Medica (2023) Vol. 65, Iss. 4
Closed Access | Times Cited: 3
Impact of ByteDance crisis communication strategies on different social media users
ShaoPeng Che, Yuanhang Zhou, Shunan Zhang, et al.
Humanities and Social Sciences Communications (2023) Vol. 10, Iss. 1
Open Access | Times Cited: 2
Deep Learning for Journalism: The Bibliometric Analysis of Deep Learning for News Production in the Artificial Intelligence Era
Richard Gordon Mayopu, Long‐Sheng Chen
Communications in computer and information science (2024), pp. 250-256
Closed Access
Sentiment Impact of Public Health Agency communication Strategies on TikTok under COVID-19 Normalization: Deep Learning Exploration
ShaoPeng Che, Jang Hyun Kim
Journal of Public Health (2023) Vol. 32, Iss. 8, pp. 1559-1570
Open Access | Times Cited: 1
A Review of Sentimental Analysis for Vaccine Dataset Using BI-LSTM Method
Alok Soreng, Safdar Sardar Khan, Arpit Deo
(2023), pp. 1-13
Closed Access
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