Dataset Card for peer_read

Dataset Summary

PearRead is a dataset of scientific peer reviews available to help researchers study this important artifact. The dataset consists of over 14K paper drafts and the corresponding accept/reject decisions in top-tier venues including ACL, NIPS and ICLR, as well as over 10K textual peer reviews written by experts for a subset of the papers.

Supported Tasks and Leaderboards

[More Information Needed]

Languages

en-English

Dataset Structure

Data Instances

[More Information Needed]

Data Fields

parsed_pdfs

• name: string Filename in the dataset
• metadata: dict Paper metadata
  • source: string Paper source
  • authors: list<string> List of paper authors
  • title: string Paper title
  • sections: list<dict> List of section heading and corresponding description
    • heading: string Section heading
    • text: string Section description
  • references: string List of references
    • title: string Title of reference paper
    • author: list<string> List of reference paper authors
    • venue: string Reference venue
    • citeRegEx: string Reference citeRegEx
    • shortCiteRegEx: string Reference shortCiteRegEx
    • year: int Reference publish year
  • referenceMentions: list<string> List of reference mentions
    • referenceID: int Reference mention ID
    • context: string Reference mention context
    • startOffset: int Reference startOffset
    • endOffset: int Reference endOffset
  • year: int Paper publish year
  • abstractText: string Paper abstract
  • creator: string Paper creator

reviews

• id: int Review ID
• conference: string Conference name
• comments: string Review comments
• subjects: string Review subjects
• version: string Review version
• date_of_submission: string Submission date
• title: string Paper title
• authors: list<string> List of paper authors
• accepted: bool Paper accepted flag
• abstract: string Paper abstract
• histories: list<string> Paper details with link
• reviews: dict Paper reviews
  • date: string Date of review
  • title: string Paper title
  • other_keys: string Reviewer other details
  • originality: string Originality score
  • comments: string Reviewer comments
  • is_meta_review: bool Review type flag
  • recommendation: string Reviewer recommendation
  • replicability: string Replicability score
  • presentation_format: string Presentation type
  • clarity: string Clarity score
  • meaningful_comparison: string Meaningful comparison score
  • substance: string Substance score
  • reviewer_confidence: string Reviewer confidence score
  • soundness_correctness: string Soundness correctness score
  • appropriateness: string Appropriateness score
  • impact: string Impact score

Data Splits

[More Information Needed]

Dataset Creation

Curation Rationale

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Source Data

Initial Data Collection and Normalization

[More Information Needed]

Who are the source language producers?

[More Information Needed]

Annotations

Annotation process

[More Information Needed]

Who are the annotators?

[More Information Needed]

Personal and Sensitive Information

[More Information Needed]

Considerations for Using the Data

Social Impact of Dataset

[More Information Needed]

Discussion of Biases

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Other Known Limitations

[More Information Needed]

Additional Information

Dataset Curators

Dongyeop Kang, Waleed Ammar, Bhavana Dalvi Mishra, Madeleine van Zuylen, Sebastian Kohlmeier, Eduard Hovy, Roy Schwartz

Licensing Information

[More Information Needed]

Citation Information

@inproceedings{kang18naacl, title = {A Dataset of Peer Reviews (PeerRead): Collection, Insights and NLP Applications}, author = {Dongyeop Kang and Waleed Ammar and Bhavana Dalvi and Madeleine van Zuylen and Sebastian Kohlmeier and Eduard Hovy and Roy Schwartz}, booktitle = {Meeting of the North American Chapter of the Association for Computational Linguistics (NAACL)}, address = {New Orleans, USA}, month = {June}, url = {https://arxiv.org/abs/1804.09635}, year = {2018} }

Contributions

Thanks to @vinaykudari for adding this dataset.