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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:

Twitter Sentiment Analysis on Coronavirus: Machine Learning Approach
Cristian Machuca, Cristian Gallardo, Renato M. Toasa
Journal of Physics Conference Series (2021) Vol. 1828, Iss. 1, pp. 012104-012104
Open Access | Times Cited: 47

Showing 1-25 of 47 citing articles:

Climate Change Sentiment Analysis Using Lexicon, Machine Learning and Hybrid Approaches
Nabila Mohamad Sham, Azlinah Mohamed
Sustainability (2022) Vol. 14, Iss. 8, pp. 4723-4723
Open Access | Times Cited: 41
Real-time Twitter Sentiment Analysis for Moroccan Universities using Machine Learning and Big Data Technologies
Imane Lasri, Anouar Riadsolh, Mourad Elbelkacemi
International Journal of Emerging Technologies in Learning (iJET) (2023) Vol. 18, Iss. 05, pp. 42-61
Open Access | Times Cited: 19
Sentiment Analysis for Political Debates on YouTube Comments using BERT Labeling, Random Oversampling, and Multinomial Naïve Bayes
Apriandy Angdresey, Lanny Sitanayah, Ignatius Lucky Henokh Tangka
Journal of Computing Theories and Applications (2025) Vol. 2, Iss. 3, pp. 342-354
Closed Access
Sentiment analysis with ensemble and machine learning methods in multi-domain datasets
Muhammet Sinan Başarslan, Fatih Kayaalp
Turkish Journal of Engineering (2022) Vol. 7, Iss. 2, pp. 141-148
Open Access | Times Cited: 16
Improving Sentiment Classification on Restaurant Reviews Using Deep Learning Models
Ratna Patil, Yadvendra Pratap Singh, Shitalkumar Adhar Rawandale, et al.
Procedia Computer Science (2024) Vol. 235, pp. 3246-3256
Open Access | Times Cited: 2
Sentimental analysis of COVID-19 twitter data using deep learning and machine learning models
Simran Darad, Sridhar Krishnan
Ingenius (2023), Iss. 29, pp. 108-117
Open Access | Times Cited: 6
Twitter Sentiment Analysis with Machine Learning
M. Jagadeesan, T. Saravanan, P.A. Selvaraj, et al.
2022 International Conference on Automation, Computing and Renewable Systems (ICACRS) (2022), pp. 681-686
Closed Access | Times Cited: 9
An Ensemble Classification of Mental Health in Malaysia related to the Covid-19 Pandemic using Social Media Sentiment Analysis
A. St Aisyah Nur, Zakaria Binti, Muneer Ahmad, et al.
KSII Transactions on Internet and Information Systems (2024) Vol. 18, Iss. 2
Open Access | Times Cited: 1
Mining the Cause of Political Decision-Making from Social Media: A Case Study of COVID-19 Policies across the US States
Zhijing Jin, Zeyu Peng, Tejas Vaidhya, et al.
(2021), pp. 288-301
Open Access | Times Cited: 12
Trends in Language Use During the COVID-19 Pandemic and Relationship Between Language Use and Mental Health: Text Analysis Based on Free Responses From a Longitudinal Study
Rachel Weger, Juan Antonio Lossio-Ventura, Margaret Rose-McCandlish, et al.
JMIR Mental Health (2022) Vol. 10, pp. e40899-e40899
Open Access | Times Cited: 8
Sentiment analysis using a deep ensemble learning model
Muhammet Sinan Başarslan, Fatih Kayaalp
Multimedia Tools and Applications (2023) Vol. 83, Iss. 14, pp. 42207-42231
Closed Access | Times Cited: 4
Sentiment analysis of coronavirus data with ensemble and machine learning methods
Muhammet Sinan Başarslan, Fatih Kayaalp
Turkish Journal of Engineering (2024) Vol. 8, Iss. 2, pp. 175-185
Open Access | Times Cited: 1
KLASIFIKASI PERSEPSI PENGGUNA TWITTER TERHADAP KASUS COVID-19 MENGGUNAKAN METODE LOGISTIC REGRESSION
Aloysius Kurniawan Santoso, Astrid Noviriandini, Aliyah Kurniasih, et al.
Jurnal Informatika Kaputama (JIK) (2021) Vol. 5, Iss. 2, pp. 234-241
Open Access | Times Cited: 11
Twitter Sentiment Analysis Based on Neural Network Techniques
Ashutosh Singal, Michael Moses Thiruthuvanathan
Lecture notes on data engineering and communications technologies (2022), pp. 33-48
Closed Access | Times Cited: 6
Exploring the nexus between food and veg*n lifestyle via text mining-based online community analytics
Ra Yoo, Seo-Young Kim, Dohee Kim, et al.
Food Quality and Preference (2022) Vol. 104, pp. 104714-104714
Closed Access | Times Cited: 6
Comprehensive sentimental analysis of tweets towards COVID-19 in Pakistan: a study on governmental preventive measures
Muhammad Faisal Ali, Rabia Irfan, Tahira Anwar Lashari
PeerJ Computer Science (2023) Vol. 9, pp. e1220-e1220
Open Access | Times Cited: 3
Deep learning modeling of public’s sentiments towards temporal evolution of COVID-19 transmission
Ying Wang, Alvin Wei Ze Chew, Limao Zhang
Applied Soft Computing (2022) Vol. 131, pp. 109728-109728
Open Access | Times Cited: 5
Pendekatan Ensemble untuk Analisis Sentimen Covid19 Menggunakan Pengklasifikasi Soft Voting
Nova Agustina, Candra Nur Ihsan
Jurnal Teknologi Informasi dan Ilmu Komputer (2023) Vol. 10, Iss. 2, pp. 263-263
Open Access | Times Cited: 2
Investigating Gender-Specific Discourse about Online Learning during COVID-19 on Twitter using Sentiment Analysis, Subjectivity Analysis, and Toxicity Analysis
Nirmalya Thakur, Shuqi Cui, Karam Khanna, et al.
(2023)
Open Access | Times Cited: 2
An Accuracy Based Comparative Study on Different Techniques and Challenges for Sentiment Analysis
Radha Krishna Jana, Saikat Maity
Lecture notes in networks and systems (2022), pp. 601-619
Closed Access | Times Cited: 4
Associations between emotions expressed in internet news and subsequent emotional content on twitter
Eric Mayor, Marcel Miché, Roselind Lieb
Heliyon (2022) Vol. 8, Iss. 12, pp. e12133-e12133
Open Access | Times Cited: 4
A Comparative Study of Sentiment Analysis Tools
Nabanita Das, Saloni Gupta, Srinjoy Das, et al.
2022 International Conference on Innovative Computing, Intelligent Communication and Smart Electrical Systems (ICSES) (2021), pp. 1-7
Closed Access | Times Cited: 5
Multihead Text Mining from COVID‐19 Feedback Using Machine Learning, Deep Learning, and Hybrid Deep Learning Approaches
Khadijatul Kobra, Samrina Sarkar Sammi, Naimur Rahman, et al.
Journal of Sensors (2024) Vol. 2024, Iss. 1
Open Access
Innovación en métodos de enseñanza en la carrera de Enfermería
María Cristina Yaselga Antamba, Ana Karina Duque Jauregui
Revista Interdisciplinaria de Educación, Salud, Actividad Física y Deporte. (2024) Vol. 1, Iss. 1, pp. 63-84
Closed Access
Fine grained sentiment analysis on microblogs based on graph convolution and self attention graph pooling
Yuanyuan Li, Baolong Zhou, Yijie Niu, et al.
Applied Intelligence (2024) Vol. 55, Iss. 2
Closed Access
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