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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:

SC-Com: Spotting Collusive Community in Opinion Spam Detection
Hyungho Byun, Sihyun Jeong, Chong-kwon Kim
Information Processing & Management (2021) Vol. 58, Iss. 4, pp. 102593-102593
Closed Access | Times Cited: 28

Showing 1-25 of 28 citing articles:

RHGNN: Fake reviewer detection based on reinforced heterogeneous graph neural networks
Jun Zhao, Minglai Shao, Hailiang Tang, et al.
Knowledge-Based Systems (2023) Vol. 280, pp. 111029-111029
Closed Access | Times Cited: 14
A robust rank aggregation framework for collusive disturbance based on community detection
Dongmei Chen, Yu Xiao, Jun Wu, et al.
Information Processing & Management (2025) Vol. 62, Iss. 4, pp. 104096-104096
Closed Access
Synthesizing global and local perspectives in contrastive learning for graph anomaly detection
Qiqi Yang, Hang Yu, Zhengyang Liu, et al.
Knowledge-Based Systems (2025), pp. 113289-113289
Closed Access
Detecting collusive spammers with heterogeneous graph attention network
Fuzhi Zhang, Jiayi Wu, Peng Zhang, et al.
Information Processing & Management (2023) Vol. 60, Iss. 3, pp. 103282-103282
Closed Access | Times Cited: 11
Temporal burstiness and collaborative camouflage aware fraud detection
Zheng Zhang, Jun Wan, Mingyang Zhou, et al.
Information Processing & Management (2022) Vol. 60, Iss. 2, pp. 103170-103170
Closed Access | Times Cited: 18
Graph Learning for Fake Review Detection
Shuo Yu, Jing Ren, Shihao Li, et al.
Frontiers in Artificial Intelligence (2022) Vol. 5
Open Access | Times Cited: 16
A graph neural network approach to detect original review spammers of astroturfing campaigns
Kuanchin Chen, Li‐Chen Cheng, Mei-Yun Ye, et al.
Electronic Commerce Research and Applications (2023) Vol. 62, pp. 101326-101326
Closed Access | Times Cited: 4
Collusive spam detection from Chinese community question answering sites: A collective classification framework
Lu Zhang, Mingming Xu, Zhan Bu, et al.
Information Sciences (2024) Vol. 667, pp. 120379-120379
Closed Access | Times Cited: 1
A robust rank aggregation method for malicious disturbance based on objective credit
Dongmei Chen, Yu Xiao, Huan Zhu, et al.
Applied Soft Computing (2024), pp. 112471-112471
Closed Access | Times Cited: 1
Detecting Product Review Spammers Using Principles of Big Data
Jitendra Kumar Rout, Anmol Dalmia, Santanu Kumar Rath, et al.
IEEE Transactions on Engineering Management (2021) Vol. 70, Iss. 7, pp. 2516-2527
Open Access | Times Cited: 9
Fake Restaurant Review Detection Using Deep Neural Networks with Hybrid Feature Fusion Method
Yifei Jian, Xingshu Chen, Haizhou Wang
Lecture notes in computer science (2022), pp. 133-148
Closed Access | Times Cited: 6
APSN: Adversarial Pseudo-Siamese Network for Fake News Stance Detection
Zhibo Zhou, Yang Yang, Zhoujun Li
Electronics (2023) Vol. 12, Iss. 4, pp. 1043-1043
Open Access | Times Cited: 3
Spam Reviews Detection in the Time of COVID-19 Pandemic: Background, Definitions, Methods and Literature Analysis
Ala’ M. Al-Zoubi, Antonio M. Mora, Hossam Faris
Applied Sciences (2022) Vol. 12, Iss. 7, pp. 3634-3634
Open Access | Times Cited: 5
Understanding Large-Scale Network Effects in Detecting Review Spammers
Jitendra Kumar Rout, Kshira Sagar Sahoo, Anmol Dalmia, et al.
IEEE Transactions on Computational Social Systems (2023) Vol. 11, Iss. 4, pp. 4994-5004
Open Access | Times Cited: 2
Collusive anomalies detection based on collaborative markov random field
Haoran Shi, Lixin Ji, Shuxin Liu, et al.
Intelligent Data Analysis (2022) Vol. 26, Iss. 6, pp. 1469-1485
Closed Access | Times Cited: 3
Graph anomaly detection framework based on feature enhancement and contrastive learning
Zhenhao Lei, Peng Pu
(2024), pp. 161-161
Closed Access
Spammer Group Detection Approach Based on Deep Reinforcement Learning
Chenghang Huo, J. J. Cui, Ru Ma, et al.
Lecture notes in computer science (2024), pp. 233-244
Closed Access
Towards a reliable spam detection: an ensemble classification with rejection option
Cleber Olivo, Altair O. Santin, Eduardo K. Viegas, et al.
Cluster Computing (2024) Vol. 28, Iss. 1
Closed Access
A metadata-aware detection model for fake restaurant reviews based on multimodal fusion
Yifei Jian, Xinyu Chen, Xiaoda Wang, et al.
Neural Computing and Applications (2024)
Closed Access
APSN: Adversarial Pseudo-Siamese Network for Fake News Stance Detection
Zhibo Zhou, Yang Yang, Feiran Huang, et al.
Research Square (Research Square) (2022)
Open Access | Times Cited: 1
Systematic Literature Review of Detecting Topics and Communities in Social Networks
Ömer Ayberk ŞENCAN, İsmail Atacak, İbrahim Alper Doğru
Bilişim Teknolojileri Dergisi (2022) Vol. 15, Iss. 3, pp. 317-329
Open Access | Times Cited: 1
GrFrauder: A Novel Unsupervised Clustering Algorithm for Identification Group Spam Reviewers
Rathan Kumar Chenoori, Radhika Kavuri
Ingénierie des systèmes d information (2022) Vol. 27, Iss. 6, pp. 1019-1027
Open Access | Times Cited: 1
Identifying spammer groups in consumer reviews using meta-data via bipartite graph approach
Varun Balakrishna, Subhajit Bag, Sobhan Sarkar
2021 International Conference on Data Analytics for Business and Industry (ICDABI) (2022), pp. 650-654
Closed Access | Times Cited: 1
USDSE: A Novel Method to Improve Service Reputation Based on Double-Side Evaluation
Jianmao Xiao, Jia Zeng, Miao Xu, et al.
Lecture notes in computer science (2023), pp. 484-498
Closed Access
Towards a Reliable Spam Detection: An Ensemble classification with rejection option
Cleber Olivo, Altair O. Santin, Eduardo K. Viegas, et al.
Research Square (Research Square) (2023)
Open Access
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