TU Darmstadt / ULB / TUbiblio

Revise and Resubmit: An Intertextual Model of Text-based Collaboration in Peer Review

Kuznetsov, Ilia ; Buchmann, Jan ; Eichler, Max ; Gurevych, Iryna (2022)
Revise and Resubmit: An Intertextual Model of Text-based Collaboration in Peer Review.
In: Computational Linguistics, 48 (4)
doi: 10.1162/coli_a_00455
Artikel, Bibliographie

Dies ist die neueste Version dieses Eintrags.

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: 2022
Autor(en): Kuznetsov, Ilia ; Buchmann, Jan ; Eichler, Max ; Gurevych, Iryna
Art des Eintrags: Bibliographie
Titel: Revise and Resubmit: An Intertextual Model of Text-based Collaboration in Peer Review
Sprache: Englisch
Publikationsjahr: 1 Dezember 2022
Verlag: MIT Press
Titel der Zeitschrift, Zeitung oder Schriftenreihe: Computational Linguistics
Jahrgang/Volume einer Zeitschrift: 48
(Heft-)Nummer: 4
DOI: 10.1162/coli_a_00455
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: UKP_p_PEER, UKP_p_InterText
Fachbereich(e)/-gebiet(e): 20 Fachbereich Informatik
20 Fachbereich Informatik > Ubiquitäre Wissensverarbeitung
TU-Projekte: DFG|GU798/28-1|PEER: Eine computerg
Hinterlegungsdatum: 28 Nov 2022 09:10
Letzte Änderung: 12 Mär 2024 10:03
PPN: 503803103
Zugehörige Links:
Export:
Suche nach Titel in: TUfind oder in Google

Verfügbare Versionen dieses Eintrags

Frage zum Eintrag Frage zum Eintrag

Optionen (nur für Redakteure)
Redaktionelle Details anzeigen Redaktionelle Details anzeigen