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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:

A Proposed Sentiment Analysis Deep Learning Algorithm for Analyzing COVID-19 Tweets
Harleen Kaur, Shafqat Ul Ahsaan, Bhavya Alankar, et al.
Information Systems Frontiers (2021) Vol. 23, Iss. 6, pp. 1417-1429
Open Access | Times Cited: 178

Showing 1-25 of 178 citing articles:

University students as early adopters of ChatGPT: Innovation Diffusion Study
Raghu Raman, Santanu Mandal, Payel Das, et al.
Research Square (Research Square) (2023)
Open Access | Times Cited: 52
Hybrid Deep Learning Models for Sentiment Analysis
Cach N. Dang, Marı́a N. Moreno Garcı́a, Fernando De la Prieta
Complexity (2021) Vol. 2021, Iss. 1
Open Access | Times Cited: 99
Deep Learning-Based Methods for Sentiment Analysis on Nepali COVID-19-Related Tweets
Chiranjibi Sitaula, Anish Basnet, A. Mainali, et al.
Computational Intelligence and Neuroscience (2021) Vol. 2021, pp. 1-11
Open Access | Times Cited: 93
A Hybrid Feature Extraction Method for Nepali COVID-19-Related Tweets Classification
Tej Bahadur Shahi, Chiranjibi Sitaula, Nawaraj Paudel
Computational Intelligence and Neuroscience (2022) Vol. 2022, pp. 1-11
Open Access | Times Cited: 61
A visual review of artificial intelligence and Industry 4.0 in healthcare
Sandeep K. Sood, Keshav Singh Rawat, Dheeraj Kumar
Computers & Electrical Engineering (2022) Vol. 101, pp. 107948-107948
Open Access | Times Cited: 57
Sentiment analysis on images using convolutional neural networks based Inception-V3 transfer learning approach
Gaurav Meena, Krishna Kumar Mohbey, Sunil Kumar
International Journal of Information Management Data Insights (2023) Vol. 3, Iss. 1, pp. 100174-100174
Open Access | Times Cited: 35
Twitter sentiment analysis using hybrid gated attention recurrent network
Nikhat Parveen, Prąsun Chakrabarti, Bùi Thanh Hùng, et al.
Journal Of Big Data (2023) Vol. 10, Iss. 1
Open Access | Times Cited: 34
Machine Learning Techniques for Sentiment Analysis of COVID-19-Related Twitter Data
Niklas Braig, Alina Benz, Soeren Voth, et al.
IEEE Access (2023) Vol. 11, pp. 14778-14803
Open Access | Times Cited: 29
Image-Based Sentiment Analysis Using InceptionV3 Transfer Learning Approach
Gaurav Meena, Krishna Kumar Mohbey, Sunil Kumar, et al.
SN Computer Science (2023) Vol. 4, Iss. 3
Closed Access | Times Cited: 24
A supervised deep learning-based sentiment analysis by the implementation of Word2Vec and GloVe Embedding techniques
Pranati Rakshit, Avik Sarkar
Multimedia Tools and Applications (2024)
Closed Access | Times Cited: 9
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 Systematic Literature Review and Future Perspectives for Handling Big Data Analytics in COVID-19 Diagnosis
Nagamani Tenali, G. Rama Mohan Babu
New Generation Computing (2023) Vol. 41, Iss. 2, pp. 243-280
Open Access | Times Cited: 21
Multi-channel CNN to classify Nepali COVID-19 related tweets using hybrid features
Chiranjibi Sitaula, Tej Bahadur Shahi
Journal of Ambient Intelligence and Humanized Computing (2023) Vol. 15, Iss. 3, pp. 2047-2056
Closed Access | Times Cited: 20
Social Media Platforms and User Engagement: A Multi-Platform Study on One-way Firm Sustainability Communication
Ashish Kumar Jha, Nishant Kumar Verma
Information Systems Frontiers (2023) Vol. 26, Iss. 1, pp. 177-194
Open Access | Times Cited: 18
Beyond the use of a novel Ensemble based Random Forest-BERT Model (Ens-RF-BERT) for the Sentiment Analysis of the hashtag COVID19 tweets
Boutheina Jlifi, Chaima Abidi, Claude Duvallet
Social Network Analysis and Mining (2024) Vol. 14, Iss. 1
Closed Access | Times Cited: 5
LegalT5-ABSA: a framework for aspect-based sentiment analysis of parties in legal cases using text-to-text transfer transformer
Sevda Rezaei Melal, Sepehr Rezaei Melal, Rashed Khanjani-Shiraz
International Journal of Data Science and Analytics (2025)
Closed Access
Investigating Influential COVID-19 Perspectives: A Multifaceted Analysis of Twitter Discourse
Shahid Bashir, Hossein Shirazi, Noushin Salek Faramarzi, et al.
Lecture notes in computer science (2025), pp. 3-22
Closed Access
Automated Classification of Societal Sentiments on Twitter With Machine Learning
Piyush Vyas, Martin Reisslein, Bhaskar Prasad Rimal, et al.
IEEE Transactions on Technology and Society (2021) Vol. 3, Iss. 2, pp. 100-110
Closed Access | Times Cited: 39
Exploring the Performance of Ensemble Machine Learning Classifiers for Sentiment Analysis of COVID-19 Tweets
Md. Mahbubar Rahman, Muhammad Nazrul Islam
Advances in intelligent systems and computing (2021), pp. 383-396
Closed Access | Times Cited: 36
Can you be Mindful? The Effectiveness of Mindfulness-Driven Interventions in Enhancing the Digital Resilience to Fake News on COVID-19
Padmali Rodrigo, Emmanuel Ogiemwonyi Arakpogun, Mai Chi Vu, et al.
Information Systems Frontiers (2022) Vol. 26, Iss. 2, pp. 501-521
Open Access | Times Cited: 27
COVID-19 Tweets Classification Based on a Hybrid Word Embedding Method
Yosra Didi, Ahlem Walha, Ali Wali
Big Data and Cognitive Computing (2022) Vol. 6, Iss. 2, pp. 58-58
Open Access | Times Cited: 26
Analysing the sentiments about the education system trough Twitter
Mary Luz Mouronte-López, Juana Savall Ceres, Aina Mora Columbrans
Education and Information Technologies (2023) Vol. 28, Iss. 9, pp. 10965-10994
Open Access | Times Cited: 15
Sentiment analysis of financial Twitter posts on Twitter with the machine learning classifiers
Handan Çam, Alper Veli Cam, Uğur Demirel, et al.
Heliyon (2023) Vol. 10, Iss. 1, pp. e23784-e23784
Open Access | Times Cited: 15
Deep Learning Model for COVID-19 Sentiment Analysis on Twitter
Salvador Contreras Hernández, María Patricia Tzili Cruz, José Martín Sánchez, et al.
New Generation Computing (2023) Vol. 41, Iss. 2, pp. 189-212
Open Access | Times Cited: 14
An interpretable hybrid predictive model of COVID-19 cases using autoregressive model and LSTM
Yangyi Zhang, Sui Tang, Yu Guo
Scientific Reports (2023) Vol. 13, Iss. 1
Open Access | Times Cited: 14
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