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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:

Detection of spam-posting accounts on Twitter
Isa Inuwa-Dutse, Mark Liptrott, Ioannis Korkontzelos
Neurocomputing (2018) Vol. 315, pp. 496-511
Open Access | Times Cited: 141

Showing 26-50 of 141 citing articles:

Detecting spammers on social network through clustering technique
Teena Jose, Suvanam Sasidhar Babu
Journal of Ambient Intelligence and Humanized Computing (2019)
Closed Access | Times Cited: 36
Spam detection on Twitter using a support vector machine and users’ features by identifying their interactions
Saleh Beyt Sheikh Ahmad, Mahnaz Rafie, Seyed Mojtaba Ghorabie
Multimedia Tools and Applications (2021) Vol. 80, Iss. 8, pp. 11583-11605
Closed Access | Times Cited: 30
Knowledge augmented transformer for adversarial multidomain multiclassification multimodal fake news detection
Chenguang Song, Nianwen Ning, Yunlei Zhang, et al.
Neurocomputing (2021) Vol. 462, pp. 88-100
Closed Access | Times Cited: 29
TwitterGAN: robust spam detection in twitter using novel generative adversarial networks
Mohammad Diqi
International Journal of Information Technology (2023) Vol. 15, Iss. 6, pp. 3103-3111
Closed Access | Times Cited: 11
Integrating statistical and visual analytic methods for bot identification of health-related survey data
Annie Chen, Midori Komi, Sierrah Bessler, et al.
Journal of Biomedical Informatics (2023) Vol. 144, pp. 104439-104439
Closed Access | Times Cited: 11
A novel deep learning model-based optimization algorithm for text message spam detection
Lipsa Das, Laxmi Ahuja, Adesh Pandey
The Journal of Supercomputing (2024) Vol. 80, Iss. 12, pp. 17823-17848
Closed Access | Times Cited: 4
Online Social Deception and Its Countermeasures: A Survey
Zhen Guo, Jin-Hee Cho, Ing-Ray Chen, et al.
IEEE Access (2020) Vol. 9, pp. 1770-1806
Open Access | Times Cited: 31
Enhanced Twitter bot detection using ensemble machine learning
Hrushikesh Shukla, Nakshatra Jagtap, Balaji Patil
(2021), pp. 930-936
Closed Access | Times Cited: 26
Cost-Based Heterogeneous Learning Framework for Real-Time Spam Detection in Social Networks With Expert Decisions
Jaeun Choi, Chunmi Jeon
IEEE Access (2021) Vol. 9, pp. 103573-103587
Open Access | Times Cited: 25
Toward a new approach to author profiling based on the extraction of statistical features
Sarra Ouni, Fethi Fkih, Mohamed Nazih Omri
Social Network Analysis and Mining (2021) Vol. 11, Iss. 1
Closed Access | Times Cited: 23
Application of ensemble Machine Learning models for phishing detection on web networks
Navyah Puri, Pranay Saggar, Amandeep Kaur, et al.
2022 Fifth International Conference on Computational Intelligence and Communication Technologies (CCICT) (2022), pp. 296-303
Closed Access | Times Cited: 17
Unsupervised collective-based framework for dynamic retraining of supervised real-time spam tweets detection model
Mahdi Washha, Aziz Qaroush, Manel Mezghani, et al.
Expert Systems with Applications (2019) Vol. 135, pp. 129-152
Open Access | Times Cited: 28
Exploring the Potential of Twitter to Understand Traffic Events and Their Locations in Greater Mumbai, India
Rahul Deb Das, Ross S. Purves
IEEE Transactions on Intelligent Transportation Systems (2019) Vol. 21, Iss. 12, pp. 5213-5222
Open Access | Times Cited: 26
A multilevel clustering technique for community detection
Isa Inuwa-Dutse, Mark Liptrott, Ioannis Korkontzelos
Neurocomputing (2021) Vol. 441, pp. 64-78
Open Access | Times Cited: 20
Spam message detection using Danger theory and Krill herd optimization
Aakanksha Sharaff, C.W.Rabiatul Adawitah C.W. Kamal, Siddhartha Porwal, et al.
Computer Networks (2021) Vol. 199, pp. 108453-108453
Closed Access | Times Cited: 20
Dataset of Arabic spam and ham tweets
Sanaa Kaddoura, Safaa Henno
Data in Brief (2023) Vol. 52, pp. 109904-109904
Open Access | Times Cited: 8
Deep Learning Based Cross Domain Sentiment Classification for Urdu Language
Amna Altaf, Muhammad Waqas Anwar, Muhammad Hasan Jamal, et al.
IEEE Access (2022) Vol. 10, pp. 102135-102147
Open Access | Times Cited: 13
Detection of Fake Users in Twitter Using Network Representation and NLP
Manojit Chakraborty, Shubham Das, Radhika Mamidi
(2022), pp. 754-758
Open Access | Times Cited: 9
KPI-HGNN: Key provenance identification based on a heterogeneous graph neural network for big data access control
Dibin Shan, Xuehui Du, Wenjuan Wang, et al.
Information Sciences (2023) Vol. 659, pp. 120059-120059
Closed Access | Times Cited: 5
“TwitterSpamDetector”
Abdullah Talha Kabakuş, Resul Kara
International Journal of Knowledge and Systems Science (2019) Vol. 10, Iss. 3, pp. 1-14
Closed Access | Times Cited: 13
SOCIAL MEDIA FOR MEDICAL JOURNALS
Sakir Ahmed, Latika Gupta
Central Asian Journal of Medical Hypotheses and Ethics (2020) Vol. 1, Iss. 1, pp. 26-32
Closed Access | Times Cited: 12
Hyperparameter tuning of AdaBoost algorithm for social spammer identification
R. Krithiga, E. Ilavarasan
International Journal of Pervasive Computing and Communications (2021) Vol. 17, Iss. 5, pp. 462-482
Closed Access | Times Cited: 11
Tracing Policy-relevant Information in Social Media: The Case of Twitter before and during the COVID-19 Crisis
Simon Vydra, Jarosław Kantorowicz
Statistics Politics and Policy (2021) Vol. 12, Iss. 1, pp. 87-127
Open Access | Times Cited: 11
An Internet Water Army Detection Supernetwork Model
Ying Lian, Xuefan Dong, Yuxue Chi, et al.
IEEE Access (2019) Vol. 7, pp. 55108-55120
Open Access | Times Cited: 11
Tweet and Account Based Spam Detection on Twitter
Kübra Nur Güngör, O. Ayhan Erdem, İbrahim Alper Doğru
Lecture notes on data engineering and communications technologies (2020), pp. 898-905
Closed Access | Times Cited: 11

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