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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:

An unsupervised method for social network spammer detection based on user information interests
Darshika Koggalahewa, Yue Xu, Ernest Foo
Journal Of Big Data (2022) Vol. 9, Iss. 1
Open Access | Times Cited: 23

Showing 23 citing articles:

Advancements and Challenges in Machine Learning: A Comprehensive Review of Models, Libraries, Applications, and Algorithms
Shahid Tufail, Hugo Riggs, Mohd Tariq, et al.
Electronics (2023) Vol. 12, Iss. 8, pp. 1789-1789
Open Access | Times Cited: 89
Machine learning-based social media bot detection: a comprehensive literature review
Malak Aljabri, Rachid Zagrouba, Afrah Shaahid, et al.
Social Network Analysis and Mining (2023) Vol. 13, Iss. 1
Open Access | Times Cited: 52
Advancing toxicity studies of per- and poly-fluoroalkyl substances (pfass) through machine learning: Models, mechanisms, and future directions
Lingxuan Meng, Beihai Zhou, Haijun Liu, et al.
The Science of The Total Environment (2024) Vol. 946, pp. 174201-174201
Closed Access | Times Cited: 9
A Combined Text-Based and Metadata-Based Deep-Learning Framework for the Detection of Spam Accounts on the Social Media Platform Twitter
Atheer S. Alhassun, Murad A. Rassam
Processes (2022) Vol. 10, Iss. 3, pp. 439-439
Open Access | Times Cited: 30
Systematic Literature Review of Social Media Bots Detection Systems
Zineb Ellaky, Faouzia Benabbou, Sara Ouahabi
Journal of King Saud University - Computer and Information Sciences (2023) Vol. 35, Iss. 5, pp. 101551-101551
Open Access | Times Cited: 18
Impact of detection accuracy rates on phishing email spikes: Towards more effective mitigation
Sunday Eric Adewumi, Uchenna Ani
Information Security Journal A Global Perspective (2025), pp. 1-38
Open Access
Unsupervised Twitter Social Bot Detection Using Deep Contrastive Graph Clustering
Xiujuan Wang, Keke Wang, Kangmiao Chen, et al.
Knowledge-Based Systems (2024) Vol. 293, pp. 111690-111690
Closed Access | Times Cited: 4
AI-based Spam Detection Techniques for Online Social Networks: Challenges and Opportunities
Azza A. Abdo, Khaznah Alhajri, Assail Alyami, et al.
Journal of Internet Services and Information Security (2023) Vol. 13, Iss. 3, pp. 78-103
Open Access | Times Cited: 5
MulBot: Unsupervised Bot Detection Based on Multivariate Time Series
Lorenzo Mannocci, Stefano Cresci, Anna Monreale, et al.
2021 IEEE International Conference on Big Data (Big Data) (2022), pp. 1485-1494
Open Access | Times Cited: 8
A Multilayered Preprocessing Approach for Recognition and Classification of Malicious Social Network Messages
Aušra Čepulionytė, Jevgenijus Toldinas, Borisas Lozinskis
Electronics (2023) Vol. 12, Iss. 18, pp. 3785-3785
Open Access | Times Cited: 3
SEBD: A Stream Evolving Bot Detection Framework with Application of PAC Learning Approach to Maintain Accuracy and Confidence Levels
Eiman Alothali, Kadhim Hayawi, Hany Alashwal
Applied Sciences (2023) Vol. 13, Iss. 7, pp. 4443-4443
Open Access | Times Cited: 2
Behaviour and Bot Analysis on Online Social Networks
Sanaz Adel Alipour, Rita Orji, A. Nur Zincir‐Heywood
International Journal of Technology and Human Interaction (2023) Vol. 19, Iss. 1, pp. 1-19
Open Access | Times Cited: 2
Enhancing detection of malicious profiles and spam tweets with an automated honeypot framework powered by deep learning
Fatna Elmendili, Mohammed Fattah, Nisrine Berros, et al.
International Journal of Information Security (2023) Vol. 23, Iss. 2, pp. 1359-1388
Closed Access | Times Cited: 2
Email Reading Behavior-Informed Machine Learning Model to Predict Phishing Susceptibility
Ning Xu, Jiluan Fan, Zikai Alex Wen
Lecture notes in computer science (2024), pp. 579-592
Closed Access
Fake reviews detection in e-commerce using machine learning techniques: A comparative survey
Maysam Jalal, Mohsin Hasan Hussein
BIO Web of Conferences (2024) Vol. 97, pp. 00099-00099
Open Access
Towards the Future of Bot Detection: A Comprehensive Taxonomical Review and Challenges on Twitter/X
Danish Javed, N. Z. Jhanjhi, Navid Ali Khan, et al.
Computer Networks (2024), pp. 110808-110808
Closed Access
Local interpretable spammer detection model with multi-head graph channel attention network
Fuzhi Zhang, Chenghang Huo, Ru Ma, et al.
Neural Networks (2024) Vol. 184, pp. 107069-107069
Closed Access
A graph neural architecture search approach for identifying bots in social media
Georgios Tzoumanekas, Michail Chatzianastasis, Loukas Ilias, et al.
Frontiers in Artificial Intelligence (2024) Vol. 7
Open Access
NRWalk2Vec-HIN: spammer group detection based on heterogeneous information network embedding over social media
Arvind Mewada, Rupesh Kumar Dewang
The Journal of Supercomputing (2023) Vol. 80, Iss. 2, pp. 1818-1851
Closed Access | Times Cited: 1
Multi-Task Learning Framework for Detecting Hashtag Hijack Attack in Mobile Social Networks
Zheng Qu, Chen Lyu, Chi‐Hung Chi
2022 IEEE 19th International Conference on Mobile Ad Hoc and Smart Systems (MASS) (2022), pp. 90-98
Closed Access | Times Cited: 2
SPAM DETECTION AND MASKING IN SOCIAL MEDIA APPLICATIONS USING AI & ML
Vaibhav Patnaik, Udisha Kashyap, Vijay Kumar, et al.
International Research Journal of Modernization in Engineering Technology and Science (2023)
Open Access
IDENTIFYING POSSIBLE RUMOR SPREADERS ON TWITTER USING THE SVM AND FEATURE LEVEL EXTRACTION
Claudia Mei Serin Sitio, Yuliant Sibaroni, Sri Suryani Prasetiyowati
Jurnal Teknik Informatika (Jutif) (2023) Vol. 4, Iss. 3, pp. 611-618
Open Access
Analyzing the Efficacy of Bot Detection Methods on Twitter/X
Danish Javed, Noor Zaman, Navid Ali Khan, et al.
(2023)
Closed Access
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