Kuznetsov, Ilia ; Buchmann, Jan ; Eichler, Max ; Gurevych, Iryna (2024)
Revise and Resubmit: An Intertextual Model of Text-Based Collaboration in Peer Review.
In: Computational Linguistics, 2022, 48 (4)
doi: 10.26083/tuprints-00026489
Artikel, Zweitveröffentlichung, Verlagsversion
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Kurzbeschreibung (Abstract)
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.
| Typ des Eintrags: | Artikel |
|---|---|
| Erschienen: | 2024 |
| Autor(en): | Kuznetsov, Ilia ; Buchmann, Jan ; Eichler, Max ; Gurevych, Iryna |
| Art des Eintrags: | Zweitveröffentlichung |
| Titel: | Revise and Resubmit: An Intertextual Model of Text-Based Collaboration in Peer Review |
| Sprache: | Englisch |
| Publikationsjahr: | 10 Januar 2024 |
| Ort: | Darmstadt |
| Publikationsdatum der Erstveröffentlichung: | Dezember 2022 |
| Ort der Erstveröffentlichung: | Cambridge, MA |
| Verlag: | MIT Press |
| Titel der Zeitschrift, Zeitung oder Schriftenreihe: | Computational Linguistics |
| Jahrgang/Volume einer Zeitschrift: | 48 |
| (Heft-)Nummer: | 4 |
| DOI: | 10.26083/tuprints-00026489 |
| URL / URN: | https://tuprints.ulb.tu-darmstadt.de/26489 |
| Zugehörige Links: | |
| Kurzbeschreibung (Abstract): | 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. |
| Freie Schlagworte: | NLP, peer review, intertextual, revision, annotation, corpus |
| Status: | Verlagsversion |
| URN: | urn:nbn:de:tuda-tuprints-264893 |
| Zusätzliche Informationen: | Acknowledgement: Funded by the European Union (ERC, INTERTEXT, 101054961). Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or the European Research Council Executive Agency. Neither the European Union nor the granting authority can be held responsible for them. |
| Sachgruppe der Dewey Dezimalklassifikatin (DDC): | 000 Allgemeines, Informatik, Informationswissenschaft > 004 Informatik |
| Fachbereich(e)/-gebiet(e): | 20 Fachbereich Informatik 20 Fachbereich Informatik > Ubiquitäre Wissensverarbeitung |
| Hinterlegungsdatum: | 10 Jan 2024 07:52 |
| Letzte Änderung: | 12 Mär 2024 10:03 |
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| Suche nach Titel in: | TUfind oder in Google |
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