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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:

COVID-19 Public Sentiment Insights and Machine Learning for Tweets Classification
Jim Samuel, G. G. Md. Nawaz Ali, Md. Mokhlesur Rahman, et al.
Information (2020) Vol. 11, Iss. 6, pp. 314-314
Open Access | Times Cited: 124

Showing 1-25 of 124 citing articles:

What social media told us in the time of COVID-19: a scoping review
Shu‐Feng Tsao, Helen Chen, Therese Tisseverasinghe, et al.
The Lancet Digital Health (2021) Vol. 3, Iss. 3, pp. e175-e194
Open Access | Times Cited: 703
Public Perception of the COVID-19 Pandemic on Twitter: Sentiment Analysis and Topic Modeling Study
Sakun Boon‐itt, Yukolpat Skunkan
JMIR Public Health and Surveillance (2020) Vol. 6, Iss. 4, pp. e21978-e21978
Open Access | Times Cited: 426
Sentiment Analysis of COVID-19 tweets by Deep Learning Classifiers—A study to show how popularity is affecting accuracy in social media
Koyel Chakraborty, Surbhi Bhatia, Siddhartha Bhattacharyya, et al.
Applied Soft Computing (2020) Vol. 97, pp. 106754-106754
Open Access | Times Cited: 361
Cross-Cultural Polarity and Emotion Detection Using Sentiment Analysis and Deep Learning on COVID-19 Related Tweets
Ali Shariq Imran, Sher Muhammad Daudpota, Zenun Kastrati, et al.
IEEE Access (2020) Vol. 8, pp. 181074-181090
Open Access | Times Cited: 296
A performance comparison of supervised machine learning models for Covid-19 tweets sentiment analysis
Furqan Rustam, Madiha Khalid, Waqar Aslam, et al.
PLoS ONE (2021) Vol. 16, Iss. 2, pp. e0245909-e0245909
Open Access | Times Cited: 274
Applications of artificial intelligence in battling against covid-19: A literature review
Mohammad-H. Tayarani N.
Chaos Solitons & Fractals (2020) Vol. 142, pp. 110338-110338
Open Access | Times Cited: 195
Sentiment Analysis and Topic Modeling on Tweets about Online Education during COVID-19
Muhammad Mujahid, Ernesto Lee, Furqan Rustam, et al.
Applied Sciences (2021) Vol. 11, Iss. 18, pp. 8438-8438
Open Access | Times Cited: 193
Significant Applications of Machine Learning for COVID-19 Pandemic
Shashi Kushwaha, Shashi Bahl, Ashok Kumar Bagha, et al.
Journal of Industrial Integration and Management (2020) Vol. 05, Iss. 04, pp. 453-479
Closed Access | Times Cited: 171
Sentimental Analysis of COVID-19 Tweets Using Deep Learning Models
Nalini Chintalapudi, Gopi Battineni, Francesco Amenta
Infectious Disease Reports (2021) Vol. 13, Iss. 2, pp. 329-339
Open Access | Times Cited: 162
The Longest Month: Analyzing COVID-19 Vaccination Opinions Dynamics From Tweets in the Month Following the First Vaccine Announcement
Liviu‐Adrian Cotfas, Camelia Delcea, Ioan Roxin, et al.
IEEE Access (2021) Vol. 9, pp. 33203-33223
Open Access | Times Cited: 139
Review on COVID‐19 diagnosis models based on machine learning and deep learning approaches
Zaid Abdi Alkareem Alyasseri, Mohammed Azmi Al‐Betar, Iyad Abu Doush, et al.
Expert Systems (2021) Vol. 39, Iss. 3
Open Access | Times Cited: 139
Investigating COVID-19 News Across Four Nations: A Topic Modeling and Sentiment Analysis Approach
Piyush Ghasiya, Koji Okamura
IEEE Access (2021) Vol. 9, pp. 36645-36656
Open Access | Times Cited: 113
Exploring public perceptions of the COVID-19 vaccine online from a cultural perspective: Semantic network analysis of two social media platforms in the United States and China
Chen Luo, Anfan Chen, Botao Cui, et al.
Telematics and Informatics (2021) Vol. 65, pp. 101712-101712
Open Access | Times Cited: 113
The Role of Artificial Intelligence in Tackling COVID-19
Neelima Arora, Amit Kumar Banerjee, Mangamoori L Narasu
Future Virology (2020) Vol. 15, Iss. 11, pp. 717-724
Open Access | Times Cited: 101
Covid-19 sentiments in smart cities: The role of technology anxiety before and during the pandemic
Orlando Troisi, Giuseppe Fenza, Mara Grimaldi, et al.
Computers in Human Behavior (2021) Vol. 126, pp. 106986-106986
Open Access | Times Cited: 95
Feeling Positive About Reopening? New Normal Scenarios From COVID-19 US Reopen Sentiment Analytics
Jim Samuel, Md. Mokhlesur Rahman, G. G. Md. Nawaz Ali, et al.
IEEE Access (2020) Vol. 8, pp. 142173-142190
Open Access | Times Cited: 94
Sentiment Analysis of Lockdown in India During COVID-19: A Case Study on Twitter
Prasoon Gupta, Sanjay Kumar, Rajiv Ranjan Suman, et al.
IEEE Transactions on Computational Social Systems (2020) Vol. 8, Iss. 4, pp. 992-1002
Open Access | Times Cited: 93
TClustVID: A novel machine learning classification model to investigate topics and sentiment in COVID-19 tweets
Md. Shahriare Satu, Md. Imran Khan, Mufti Mahmud, et al.
Knowledge-Based Systems (2021) Vol. 226, pp. 107126-107126
Open Access | Times Cited: 87
Classification of COVID-19 individuals using adaptive neuro-fuzzy inference system
Celestine Iwendi, Kainaat Mahboob, Zarnab Khalid, et al.
Multimedia Systems (2021) Vol. 28, Iss. 4, pp. 1223-1237
Open Access | Times Cited: 76
Machine Learning on the COVID-19 Pandemic, Human Mobility and Air Quality: A Review
Md. Mokhlesur Rahman, Kamal Chandra Paul, Md. Amjad Hossain, et al.
IEEE Access (2021) Vol. 9, pp. 72420-72450
Open Access | Times Cited: 69
iResponse: An AI and IoT-Enabled Framework for Autonomous COVID-19 Pandemic Management
Furqan Alam, Ahmed Almaghthawi, Iyad Katib, et al.
Sustainability (2021) Vol. 13, Iss. 7, pp. 3797-3797
Open Access | Times Cited: 55
Socioeconomic factors analysis for COVID-19 US reopening sentiment with Twitter and census data
Md. Mokhlesur Rahman, G. G. Md. Nawaz Ali, Xue Jun Li, et al.
Heliyon (2021) Vol. 7, Iss. 2, pp. e06200-e06200
Open Access | Times Cited: 54
Applying and Understanding an Advanced, Novel Deep Learning Approach: A Covid 19, Text Based, Emotions Analysis Study
Jyoti Choudrie, Shruti Patil, Ketan Kotecha, et al.
Information Systems Frontiers (2021) Vol. 23, Iss. 6, pp. 1431-1465
Open Access | Times Cited: 54
A study on the sentiments and psychology of twitter users during COVID-19 lockdown period
Ishaani Priyadarshini, Pinaki Mohanty, Raghvendra Kumar, et al.
Multimedia Tools and Applications (2021) Vol. 81, Iss. 19, pp. 27009-27031
Open Access | Times Cited: 53
Predicting Coronavirus Pandemic in Real-Time Using Machine Learning and Big Data Streaming System
Xiongwei Zhang, Hager Saleh, Eman M. G. Younis, et al.
Complexity (2020) Vol. 2020, pp. 1-10
Open Access | Times Cited: 51
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