CorpusStudio: Surfacing Emergent Patterns In A Corpus Of Prior Work While Writing

Many communities, including the scientific community, develop implicit writing norms. Understanding them is crucial for effective communication with that community. Writers gradually develop an implicit understanding of norms by reading papers and receiving feedback on their writing. However, it is difficult to both externalize this knowledge and apply it to one's own writing. We propose two new writing support concepts that reify document and sentence-level patterns in a given text corpus: (1) an ordered distribution over section titles and (2) given the user's draft and cursor location, many retrieved contextually relevant sentences. Recurring words in the latter are algorithmically highlighted to help users see any emergent norms. Study results (N=16) show that participants revised the structure and content using these concepts, gaining confidence in aligning with or breaking norms after reviewing many examples. These results demonstrate the value of reifying distributions over other authors' writing choices during the writing process.

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Publication Details

Published
2025-04-24
DOI
https://doi.org/10.1145/3706598.3713974
Citations
2
Primary Topic
Natural Language Processing Techniques
Type
article
Field-Weighted Citation Impact
4.96

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article

CorpusStudio: Surfacing Emergent Patterns In A Corpus Of Prior Work While Writing

Chelse Swoopes, Hai Dang, Daniel Buschek, Elena L. Glassman
2 citations
Natural Language Processing Techniques
4.96
article

CorpusStudio: Surfacing Emergent Patterns In A Corpus Of Prior Work While Writing

Chelse Swoopes, Hai Dang, Daniel Buschek, Elena L. Glassman
article en
2 citations

Abstract

Many communities, including the scientific community, develop implicit writing norms. Understanding them is crucial for effective communication with that community. Writers gradually develop an implicit understanding of norms by reading papers and receiving feedback on their writing. However, it is difficult to both externalize this knowledge and apply it to one's own writing. We propose two new writing support concepts that reify document and sentence-level patterns in a given text corpus: (1) an ordered distribution over section titles and (2) given the user's draft and cursor location, many retrieved contextually relevant sentences. Recurring words in the latter are algorithmically highlighted to help users see any emergent norms. Study results (N=16) show that participants revised the structure and content using these concepts, gaining confidence in aligning with or breaking norms after reviewing many examples. These results demonstrate the value of reifying distributions over other authors' writing choices during the writing process.

Harvard University (US), University of Bayreuth (DE)
National Science Foundation, Alfred P. Sloan Foundation, Deutsche Forschungsgemeinschaft
Quality Education
Openalex Percentile: Top 6%
Natural Language Processing Techniques
4.96
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