{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,15]],"date-time":"2026-01-15T04:14:12Z","timestamp":1768450452305,"version":"3.49.0"},"reference-count":50,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2025,2,5]],"date-time":"2025-02-05T00:00:00Z","timestamp":1738713600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["72334007"],"award-info":[{"award-number":["72334007"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["BDCC"],"abstract":"<jats:p>The influence of scientific papers is measured by their citations. Although predicting the papers\u2019 citation impact based on non-content factors has garnered extensive attention, the influence of such factors is rarely compared. In this article, we compare the influence of non-content factors on the citation counts of academic publications across three fields, i.e., math, computer science, and management. We consider different methods in this study, including three machine learning approaches, namely, XGBoost, Gradient Boosting Decision Tree, and Random Forest, along with statistical techniques such as linear regression and quantile analysis. Our findings reveal that no matter the field or analytical method applied, author prestige and the number of references consistently stand out as the most influential factors, while the breadth of categories covered by the paper has minimal impact. In mathematics, the first citation date and article length are almost equally important as author prestige, while the number of authors and the journal impact factor are crucial for computer science papers. In management, the number of collaborating countries is relatively influential with respect to the paper\u2019s citations. The results of the quantile regression indicate that at higher quantile levels, the impact of author prestige and the number of authors on the papers\u2019 citation impact are more pronounced across all three disciplines, while the journal impact factor and paper length have the greatest influence at low and medium quantile levels. Our findings indicate that the reliance of academic citations on author prestige and journal impact factors not only highlights the unequal distribution of resources within the current academic system but also further exacerbates citation inequality.<\/jats:p>","DOI":"10.3390\/bdcc9020030","type":"journal-article","created":{"date-parts":[[2025,2,5]],"date-time":"2025-02-05T05:50:36Z","timestamp":1738734636000},"page":"30","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Ranking Influential Non-Content Factors on Scientific Papers\u2019 Citation Impact: A Multidomain Comparative Analysis"],"prefix":"10.3390","volume":"9","author":[{"given":"Jiannan","family":"Zhu","sequence":"first","affiliation":[{"name":"Institutes of Science and Development, Chinese Academy of Sciences, Beijing 100190, China"},{"name":"School of Public Policy and Management, University of Chinese Academy of Sciences, Beijing 100049, China"}]},{"given":"Jiayi","family":"Zhou","sequence":"additional","affiliation":[{"name":"Institutes of Science and Development, Chinese Academy of Sciences, Beijing 100190, China"},{"name":"School of Public Policy and Management, University of Chinese Academy of Sciences, Beijing 100049, China"}]},{"given":"Jiaofeng","family":"Pan","sequence":"additional","affiliation":[{"name":"Institutes of Science and Development, Chinese Academy of Sciences, Beijing 100190, China"},{"name":"School of Public Policy and Management, University of Chinese Academy of Sciences, Beijing 100049, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3062-1935","authenticated-orcid":false,"given":"Fu","family":"Gu","sequence":"additional","affiliation":[{"name":"Center of Engineering Management, Polytechnic Institute, Zhejiang University, Hangzhou 310015, China"},{"name":"Department of Industrial and System Engineering, Zhejiang University, Hangzhou 310027, China"},{"name":"National Institute of Innovation Management, Zhejiang University, Hangzhou 310027, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2201-3219","authenticated-orcid":false,"given":"Jianfeng","family":"Guo","sequence":"additional","affiliation":[{"name":"Institutes of Science and Development, Chinese Academy of Sciences, Beijing 100190, China"},{"name":"School of Public Policy and Management, University of Chinese Academy of Sciences, Beijing 100049, China"}]}],"member":"1968","published-online":{"date-parts":[[2025,2,5]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1233","DOI":"10.1007\/s11192-014-1279-6","article-title":"Citation Impact Prediction for Scientific Papers Using Stepwise Regression Analysis","volume":"101","author":"Yu","year":"2014","journal-title":"Scientometrics"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"642","DOI":"10.1016\/j.joi.2015.06.005","article-title":"Predicting the Long-Term Citation Impact of Recent Publications","volume":"9","author":"Stegehuis","year":"2015","journal-title":"J. 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