IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0259238.html
   My bibliography  Save this article

Peer review analyze: A novel benchmark resource for computational analysis of peer reviews

Author

Listed:
  • Tirthankar Ghosal
  • Sandeep Kumar
  • Prabhat Kumar Bharti
  • Asif Ekbal

Abstract

Peer Review is at the heart of scholarly communications and the cornerstone of scientific publishing. However, academia often criticizes the peer review system as non-transparent, biased, arbitrary, a flawed process at the heart of science, leading to researchers arguing with its reliability and quality. These problems could also be due to the lack of studies with the peer-review texts for various proprietary and confidentiality clauses. Peer review texts could serve as a rich source of Natural Language Processing (NLP) research on understanding the scholarly communication landscape, and thereby build systems towards mitigating those pertinent problems. In this work, we present a first of its kind multi-layered dataset of 1199 open peer review texts manually annotated at the sentence level (∼ 17k sentences) across the four layers, viz. Paper Section Correspondence, Paper Aspect Category, Review Functionality, and Review Significance. Given a text written by the reviewer, we annotate: to which sections (e.g., Methodology, Experiments, etc.), what aspects (e.g., Originality/Novelty, Empirical/Theoretical Soundness, etc.) of the paper does the review text correspond to, what is the role played by the review text (e.g., appreciation, criticism, summary, etc.), and the importance of the review statement (major, minor, general) within the review. We also annotate the sentiment of the reviewer (positive, negative, neutral) for the first two layers to judge the reviewer’s perspective on the different sections and aspects of the paper. We further introduce four novel tasks with this dataset, which could serve as an indicator of the exhaustiveness of a peer review and can be a step towards the automatic judgment of review quality. We also present baseline experiments and results for the different tasks for further investigations. We believe our dataset would provide a benchmark experimental testbed for automated systems to leverage on current NLP state-of-the-art techniques to address different issues with peer review quality, thereby ushering increased transparency and trust on the holy grail of scientific research validation. Our dataset and associated codes are available at https://www.iitp.ac.in/~ai-nlp-ml/resources.html#Peer-Review-Analyze.

Suggested Citation

  • Tirthankar Ghosal & Sandeep Kumar & Prabhat Kumar Bharti & Asif Ekbal, 2022. "Peer review analyze: A novel benchmark resource for computational analysis of peer reviews," PLOS ONE, Public Library of Science, vol. 17(1), pages 1-29, January.
    • Handle: RePEc:plo:pone00:0259238
    DOI: 10.1371/journal.pone.0259238
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0259238
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0259238&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0259238?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Giangiacomo Bravo & Francisco Grimaldo & Emilia López-Iñesta & Bahar Mehmani & Flaminio Squazzoni, 2019. "The effect of publishing peer review reports on referee behavior in five scholarly journals," Nature Communications, Nature, vol. 10(1), pages 1-8, December.
    2. Elise S. Brezis & Aliaksandr Birukou, 2020. "Arbitrariness in the peer review process," Scientometrics, Springer;Akadémiai Kiadó, vol. 123(1), pages 393-411, April.
    3. Heidi Ledford & Richard Van Noorden, 2020. "High-profile coronavirus retractions raise concerns about data oversight," Nature, Nature, vol. 582(7811), pages 160-160, June.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Wenqing Wu & Haixu Xi & Chengzhi Zhang, 2024. "Are the confidence scores of reviewers consistent with the review content? Evidence from top conference proceedings in AI," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(7), pages 4109-4135, July.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Pengfei Jia & Weixi Xie & Guangyao Zhang & Xianwen Wang, 2023. "Do reviewers get their deserved acknowledgments from the authors of manuscripts?," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(10), pages 5687-5703, October.
    2. Quan-Hoang Vuong & Tam-Tri Le & Viet-Phuong La & Huyen Thanh Thanh Nguyen & Manh-Toan Ho & Quy Khuc & Minh-Hoang Nguyen, 2022. "Covid-19 vaccines production and societal immunization under the serendipity-mindsponge-3D knowledge management theory and conceptual framework," Palgrave Communications, Palgrave Macmillan, vol. 9(1), pages 1-12, December.
    3. Sven Helmer & David B. Blumenthal & Kathrin Paschen, 2020. "What is meaningful research and how should we measure it?," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(1), pages 153-169, October.
    4. Chunli Wei & Jingyi Zhao & Jue Ni & Jiang Li, 2023. "What does open peer review bring to scientific articles? Evidence from PLoS journals," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(5), pages 2763-2776, May.
    5. Hou, Li & Wu, Qiang & Xie, Yundong, 2024. "Does open identity of peer reviewers positively relate to citations?," Journal of Informetrics, Elsevier, vol. 18(1).
    6. Zhuanlan Sun & C. Clark Cao & Sheng Liu & Yiwei Li & Chao Ma, 2024. "Behavioral consequences of second-person pronouns in written communications between authors and reviewers of scientific papers," Nature Communications, Nature, vol. 15(1), pages 1-12, December.
    7. Ying He & Kun Tian & Xiaoran Xu, 2023. "A validation study on the factors affecting the practice modes of open peer review," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(1), pages 587-607, January.
    8. Sun, Zhuanlan, 2024. "Textual features of peer review predict top-cited papers: An interpretable machine learning perspective," Journal of Informetrics, Elsevier, vol. 18(2).
    9. Elena A. Erosheva & Patrícia Martinková & Carole J. Lee, 2021. "When zero may not be zero: A cautionary note on the use of inter‐rater reliability in evaluating grant peer review," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 184(3), pages 904-919, July.
    10. Annie Collins & Rohan Alexander, 2022. "Reproducibility of COVID-19 pre-prints," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(8), pages 4655-4673, August.
    11. Jibang Wu & Haifeng Xu & Yifan Guo & Weijie Su, 2023. "A Truth Serum for Eliciting Self-Evaluations in Scientific Reviews," Papers 2306.11154, arXiv.org, revised Feb 2024.
    12. Carol Nash, 2023. "Roles and Responsibilities for Peer Reviewers of International Journals," Publications, MDPI, vol. 11(2), pages 1-24, June.
    13. Eva Barlösius & Laura Paruschke & Axel Philipps, 2024. "Peer review’s irremediable flaws: Scientists’ perspectives on grant evaluation in Germany," Research Evaluation, Oxford University Press, vol. 32(4), pages 623-634.
    14. Trenton Taros & Christopher Zoppo & Nathan Yee & Jack Hanna & Christine MacGinnis, 2023. "Retracted Covid-19 articles: significantly more cited than other articles within their journal of origin," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(5), pages 2935-2943, May.
    15. Axel Philipps, 2022. "Research funding randomly allocated? A survey of scientists’ views on peer review and lottery," Science and Public Policy, Oxford University Press, vol. 49(3), pages 365-377.
    16. Serge P J M Horbach, 2021. "No time for that now! Qualitative changes in manuscript peer review during the Covid-19 pandemic [COVID-19 Medical Papers Have Fewer Women First Authors than Expected]," Research Evaluation, Oxford University Press, vol. 30(3), pages 231-239.
    17. ederico Bianchi & Flaminio Squazzoni, 2022. "Can transparency undermine peer review? A simulation model of scientist behavior under open peer review [Reviewing Peer Review]," Science and Public Policy, Oxford University Press, vol. 49(5), pages 791-800.
    18. Xie, Yundong & Wu, Qiang & Wang, Yezhu & Hou, Li & Liu, Yuanyuan, 2024. "Does the handling time of scientific papers relate to their academic impact and social attention? Evidence from Nature, Science, and PNAS," Journal of Informetrics, Elsevier, vol. 18(2).
    19. Sun, Zhuanlan & Clark Cao, C. & Ma, Chao & Li, Yiwei, 2023. "The academic status of reviewers predicts their language use," Journal of Informetrics, Elsevier, vol. 17(4).
    20. Lu Liu & Benjamin F. Jones & Brian Uzzi & Dashun Wang, 2023. "Data, measurement and empirical methods in the science of science," Nature Human Behaviour, Nature, vol. 7(7), pages 1046-1058, July.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pone00:0259238. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.