Accès libre

A paper mill detection model based on citation manipulation paradigm

, , , ,  et   
06 janv. 2025
À propos de cet article

Citez
Télécharger la couverture

Candal-Pedreira, C., Ross, J. S., Ruano-Ravina, A., Egilman, D. S., Fernández, E., & Pérez-Ríos, M. (2022). Retracted papers originating from Paper mills: cross sectional study. bmj, 379. Candal-Pedreira C. Ross J. S. Ruano-Ravina A. Egilman D. S. Fernández E. Pérez-Ríos M. ( 2022 ). Retracted papers originating from Paper mills: cross sectional study . bmj , 379 . Search in Google Scholar

Chakraborty, J., Pradhan, D. K., & Nandi, S. (2021). On the identification and analysis of citation pattern irregularities among journals. Expert Systems, 38(4), e12561. Chakraborty J. Pradhan D. K. Nandi S. ( 2021 ). On the identification and analysis of citation pattern irregularities among journals . Expert Systems , 38 ( 4 ), e12561 . Search in Google Scholar

Chen, J., Hou, H., Gao, J., Ji, Y., & Bai, T. (2019). RGCN: recurrent graph convolutional networks for targetdependent sentiment analysis. In International Conference on Knowledge Science, Engineering and Management (pp. 667-675). Cham: Springer International Publishing. Chen J. Hou H. Gao J. Ji Y. Bai T. ( 2019 ). RGCN: recurrent graph convolutional networks for targetdependent sentiment analysis . In International Conference on Knowledge Science, Engineering and Management (pp. 667 - 675 ). Cham : Springer International Publishing . Search in Google Scholar

Christopher, J. (2021). The raw truth about Paper mills. FEBS letters, 595(13), 1751-1757. Christopher J. ( 2021 ). The raw truth about Paper mills . FEBS letters , 595 ( 13 ), 1751 - 1757 . Search in Google Scholar

da Silva, J. A. T., & Nazarovets, S. (2023). Assessment of retracted papers, and their retraction notices, from a cancer journal associated with “Paper mills”. Journal of Data and Information Science, 8(2), 118-125. da Silva J. A. T. Nazarovets S. ( 2023 ). Assessment of retracted papers, and their retraction notices, from a cancer journal associated with “Paper mills” . Journal of Data and Information Science , 8 ( 2 ), 118 - 125 . Search in Google Scholar

Devlin, J., Chang, M. W., Lee, K., & Toutanova, K. (2018). Bert: Pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805. Devlin J. Chang M. W. Lee K. Toutanova K. ( 2018 ). Bert: Pre-training of deep bidirectional transformers for language understanding . arXiv preprint arXiv:1810.04805 . Search in Google Scholar

Else, H., & Van Noorden, R. (2021). The fight against fake-paper factories that churn out sham science. Nature, 591(7851), 516-520. Else H. Van Noorden R. ( 2021 ). The fight against fake-paper factories that churn out sham science . Nature , 591 ( 7851 ), 516 - 520 . Search in Google Scholar

Else, H. (2022). ‘Papermill alarm’software flags potentially fake papers. Else H. ( 2022 ). ‘Papermill alarm’software flags potentially fake papers . Search in Google Scholar

Hu, Z., Dong, Y., Wang, K., & Sun, Y. (2020). Heterogeneous graph transformer. In Proceedings of the web conference 2020 (pp. 2704-2710). Hu Z. Dong Y. Wang K. Sun Y. ( 2020 ). Heterogeneous graph transformer . In Proceedings of the web conference 2020 (pp. 2704 - 2710 ). Search in Google Scholar

Ke, G., Meng, Q., Finley, T., Wang, T., Chen, W., Ma, W., … & Liu, T. Y. (2017). Lightgbm: A highly efficient gradient boosting decision tree. Advances in neural information processing systems, 30. Ke G. Meng Q. Finley T. Wang T. Chen W. Ma W. Liu T. Y. ( 2017 ). Lightgbm: A highly efficient gradient boosting decision tree . Advances in neural information processing systems , 30 . Search in Google Scholar

Liu, Q., Barhoumi, A., & Labbé, C. (2024). Miscitations in scientific papers: dataset and detection. Liu Q. Barhoumi A. Labbé C. ( 2024 ). Miscitations in scientific papers: dataset and detection . Search in Google Scholar

Oransky, I. (2022). Nearing 5,000 retractions: A review of 2022. Retraction Watch. https://retractionwatch. com/2022/12/27/nearing-5000-retractions-a-review-of-2022/ Oransky I. ( 2022 ). Nearing 5,000 retractions: A review of 2022 . Retraction Watch . https://retractionwatch.com/2022/12/27/nearing-5000-retractions-a-review-of-2022/ Search in Google Scholar

Rogerson, A. M. (2014). Detecting the work of essay mills and file swapping sites: some clues they leave behind. Rogerson A. M. ( 2014 ). Detecting the work of essay mills and file swapping sites: some clues they leave behind . Search in Google Scholar

Seifert, R. (2021). How Naunyn-Schmiedeberg’s Archives of Pharmacology deals with fraudulent papers from Paper mills. Naunyn-schmiedeberg’s Archives of Pharmacology, 394, 431-436. Seifert R. ( 2021 ). How Naunyn-Schmiedeberg’s Archives of Pharmacology deals with fraudulent papers from Paper mills . Naunyn-schmiedeberg’s Archives of Pharmacology , 394 , 431 - 436 . Search in Google Scholar

Van Noorden, R. (2023). How big is science’s fake-paper problem?. Nature, 623(7987), 466-467. Van Noorden R. ( 2023 ). How big is science’s fake-paper problem? . Nature , 623 ( 7987 ), 466 - 467 . Search in Google Scholar

Wang, X., Ji, H., Shi, C., Wang, B., Ye, Y., Cui, P., & Yu, P. S. (2019). Heterogeneous graph attention network. In The world wide web conference (pp. 2022-2032). Wang X. Ji H. Shi C. Wang B. Ye Y. Cui P. Yu P. S. ( 2019 ). Heterogeneous graph attention network . In The world wide web conference (pp. 2022 - 2032 ). Search in Google Scholar

Wang, K., Shen, W., Yang, Y., Quan, X., & Wang, R. (2020). Relational graph attention network for aspect-based sentiment analysis. arXiv preprint arXiv:2004.12362. Wang K. Shen W. Yang Y. Quan X. Wang R. ( 2020 ). Relational graph attention network for aspect-based sentiment analysis . arXiv preprint arXiv:2004.12362 . Search in Google Scholar

Wittau, J., Celik, S., Kacprowski, T., Deserno, T. M., & Seifert, R. (2024). Fake paper identification in the pool of withdrawn and rejected manuscripts submitted to Naunyn–Schmiedeberg’s Archives of Pharmacology. Naunynschmiedeberg’s Archives of Pharmacology, 397(4), 2171-2181. Wittau J. Celik S. Kacprowski T. Deserno T. M. Seifert R. ( 2024 ). Fake paper identification in the pool of withdrawn and rejected manuscripts submitted to Naunyn–Schmiedeberg’s Archives of Pharmacology . Naunynschmiedeberg’s Archives of Pharmacology , 397 ( 4 ), 2171 - 2181 . Search in Google Scholar

Xu, K., Hu, W., Leskovec, J., & Jegelka, S. (2018). How powerful are graph neural networks?. arXiv preprint arXiv:1810.00826. Xu K. Hu W. Leskovec J. Jegelka S. ( 2018 ). How powerful are graph neural networks? . arXiv preprint arXiv:1810.00826 . Search in Google Scholar

Zhang, Y., Jin, R., & Zhou, Z. H. (2010). Understanding bag-of-words model: a statistical framework. International journal of machine learning and cybernetics, 1, 43-52. Zhang Y. Jin R. Zhou Z. H. ( 2010 ). Understanding bag-of-words model: a statistical framework . International journal of machine learning and cybernetics , 1 , 43 - 52 Search in Google Scholar