PolitePEER: does peer review hurt? A dataset to gauge politeness intensity in the peer reviews.

Even though peer review is a central aspect of scientific communication, research shows that the process reveals a power imbalance. The position of the reviewer allows them to be harsh and intentionally offensive without being held accountable. It casts doubt on the integrity of the peer-review proc...

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Publicado en:Language Resources & Evaluation Vol. 58; no. 4; pp. 1291 - 1314
Autores principales: Bharti, Prabhat Kumar, Navlakha, Meith, Agarwal, Mayank, Ekbal, Asif
Formato: Artículo
Publicado: Springer Nature Dec2024
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Dec2024
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      pub: Springer Nature
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        atl: PolitePEER: does peer review hurt? A dataset to gauge politeness intensity in the peer reviews.
      aug:
        au:
          Bharti, Prabhat Kumar
          Navlakha, Meith
          Agarwal, Mayank
          Ekbal, Asif
        affil:
          Department of Computer Science and Engineering, Indian Institute of Technology, Bihta, 801106, Patna, Bihar, India
          https://ror.org/04d4hxn32 Department of Computer Engineering, Dwarkadas J. Sanghvi College of Engineering, 400056, Mumbai, Maharashtra, India
      su:
        Scientific communication
        Courtesy
        Computer performance
        Offensive behavior
        Professionalism
        Digital libraries
      sug:
        subj:
          Scientific communication
          Courtesy
          Computer performance
          Offensive behavior
          Professionalism
          Digital libraries
      keyword:
        Dataset applications
        Politeness scaling
        Review comments
      ab: Even though peer review is a central aspect of scientific communication, research shows that the process reveals a power imbalance. The position of the reviewer allows them to be harsh and intentionally offensive without being held accountable. It casts doubt on the integrity of the peer-review process and transforms it into an unpleasant and traumatic experience for authors. Accordingly, more effort should be given to provide critical and constructive feedback. Hence, it is necessary to remedy the growing rudeness and lack of professionalism in the review system, by analyzing the tone of review comments and creating a classification on the level of politeness in a review comment. To this end, we develop the first annotated PolitePEER dataset encompassing five levels of politeness: (1) highly impolite, (2) impolite, (3) neutral, (4) polite, and (5) highly polite. The review sentences accrued from multiple venues, viz., ICLR, NeurIPS, Publons and ShitMyReviewersSay. We have formulated our annotation guidelines and conducted a thorough analysis of the PolitePEER dataset, ensuring the dataset quality with an inter-annotation agreement of 93%. Additionally, we have benchmarked PolitePEER for multiclass classification and provided an extensive analysis of the proposed baseline. As a result, the proposed PolitePEER can aid in developing a politeness indicator to notify the reviewer and the editors to amend and formalize the review accordingly. Our dataset and codes are available at https://github.com/PrabhatkrBharti/PolitePEER.git for the community to explore further.
      pubtype: Academic Journal
      doctype: Article
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    language: English
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      custom: Language Resources & Evaluation is a copyright of Springer, 2024. All Rights Reserved.
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