Revise and Resubmit: An Intertextual Model of Text-based Collaboration in Peer Review
Peer review is a key component of the publishing process in most fields of science. Increasing submission rates put a strain on reviewing quality and efficiency, motivating the development of applications to support the reviewing and editorial work. While existing NLP studies focus on the analysis o...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
The MIT Press
2022-08-01
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| Series: | Computational Linguistics |
| Online Access: | http://dx.doi.org/10.1162/coli_a_00455 |
| _version_ | 1797795433980887040 |
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| author | Ilia Kuznetsov Jan Buchmann Max Eichler Iryna Gurevych |
| author_facet | Ilia Kuznetsov Jan Buchmann Max Eichler Iryna Gurevych |
| author_sort | Ilia Kuznetsov |
| collection | DOAJ |
| description | Peer review is a key component of the publishing process in most fields of science. Increasing submission rates put a strain on reviewing quality and efficiency, motivating the development of applications to support the reviewing and editorial work. While existing NLP studies focus on the analysis of individual texts, editorial assistance often requires modeling interactions between pairs of texts—yet general frameworks and datasets to support this scenario are missing. Relationships between texts are the core object of the intertextuality theory—a family of approaches in literary studies not yet operationalized in NLP. Inspired by prior theoretical work, we propose the first intertextual model of text-based collaboration, which encompasses three major phenomena that make up a full iteration of the review–revise–and–resubmit cycle: pragmatic tagging, linking, and long-document
version alignment. While peer review is used across the fields of science and publication formats, existing datasets solely focus on conference-style review in computer science. Addressing this, we instantiate our proposed model in the first annotated multidomain corpus in journal-style post-publication open peer review, and provide detailed insights into the practical aspects of intertextual annotation. Our resource is a major step toward multidomain, fine-grained applications of NLP in editorial support for peer review, and our intertextual framework paves the path for general-purpose modeling of text-based collaboration. We make our corpus, detailed annotation guidelines, and accompanying code publicly available.1 |
| first_indexed | 2024-03-13T03:17:52Z |
| format | Article |
| id | doaj.art-253988e94b0746eda984ede06d09c3cb |
| institution | Directory Open Access Journal |
| issn | 1530-9312 |
| language | English |
| last_indexed | 2024-03-13T03:17:52Z |
| publishDate | 2022-08-01 |
| publisher | The MIT Press |
| record_format | Article |
| series | Computational Linguistics |
| spelling | doaj.art-253988e94b0746eda984ede06d09c3cb2023-06-25T14:50:05ZengThe MIT PressComputational Linguistics1530-93122022-08-0148410.1162/coli_a_00455Revise and Resubmit: An Intertextual Model of Text-based Collaboration in Peer ReviewIlia KuznetsovJan BuchmannMax EichlerIryna GurevychPeer review is a key component of the publishing process in most fields of science. Increasing submission rates put a strain on reviewing quality and efficiency, motivating the development of applications to support the reviewing and editorial work. While existing NLP studies focus on the analysis of individual texts, editorial assistance often requires modeling interactions between pairs of texts—yet general frameworks and datasets to support this scenario are missing. Relationships between texts are the core object of the intertextuality theory—a family of approaches in literary studies not yet operationalized in NLP. Inspired by prior theoretical work, we propose the first intertextual model of text-based collaboration, which encompasses three major phenomena that make up a full iteration of the review–revise–and–resubmit cycle: pragmatic tagging, linking, and long-document version alignment. While peer review is used across the fields of science and publication formats, existing datasets solely focus on conference-style review in computer science. Addressing this, we instantiate our proposed model in the first annotated multidomain corpus in journal-style post-publication open peer review, and provide detailed insights into the practical aspects of intertextual annotation. Our resource is a major step toward multidomain, fine-grained applications of NLP in editorial support for peer review, and our intertextual framework paves the path for general-purpose modeling of text-based collaboration. We make our corpus, detailed annotation guidelines, and accompanying code publicly available.1http://dx.doi.org/10.1162/coli_a_00455 |
| spellingShingle | Ilia Kuznetsov Jan Buchmann Max Eichler Iryna Gurevych Revise and Resubmit: An Intertextual Model of Text-based Collaboration in Peer Review Computational Linguistics |
| title | Revise and Resubmit: An Intertextual Model of Text-based Collaboration in Peer Review |
| title_full | Revise and Resubmit: An Intertextual Model of Text-based Collaboration in Peer Review |
| title_fullStr | Revise and Resubmit: An Intertextual Model of Text-based Collaboration in Peer Review |
| title_full_unstemmed | Revise and Resubmit: An Intertextual Model of Text-based Collaboration in Peer Review |
| title_short | Revise and Resubmit: An Intertextual Model of Text-based Collaboration in Peer Review |
| title_sort | revise and resubmit an intertextual model of text based collaboration in peer review |
| url | http://dx.doi.org/10.1162/coli_a_00455 |
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