Spotting Suspicious Academic Citations Using Self-Learning Graph Transformers

The study introduces a novel approach to identify potential citation manipulation within academic papers. This method utilizes perturbations of a deep embedding model, integrating Graph-Masked Autoencoders to merge textual information with evidence of graph connectivity. Consequently, it yields a mo...

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Bibliographic Details

Published in:	Mathematics (Basel) Vol. 12; no. 6; p. 814
Main Authors:	Avros, Renata, Haim, Mor Ben, Madar, Almog, Ravve, Elena, Volkovich, Zeev
Format:	Journal Article
Language:	English
Published:	Basel MDPI AG 01.03.2024
Subjects:	Analysis Citations Computational linguistics Credibility Design Electric transformers Graph representations Graph theory graph-masked autoencoders Language processing manipulated citations Natural language interfaces network perturbation Perturbation
ISSN:	2227-7390, 2227-7390
Online Access:	Get full text
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