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        <title>What Makes Writing Great? First Experiments on Article Quality Prediction in the Science Journalism Domain</title>
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    <name type="personal">
        <namePart type="given">Annie</namePart>
        <namePart type="family">Louis</namePart>
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    <abstract>Great writing is rare and highly admired. Readers seek out articles that are beautifully written, informative and entertaining. Yet information-access technologies lack capabilities for predicting article quality at this level. In this paper we present first experiments on article quality prediction in the science journalism domain. We introduce a corpus of great pieces of science journalism, along with typical articles from the genre. We implement features to capture aspects of great writing, including surprising, visual and emotional content, as well as general features related to discourse organization and sentence structure. We show that the distinction between great and typical articles can be detected fairly accurately, and that the entire spectrum of our features contribute to the distinction.</abstract>
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    <identifier type="doi">10.1162/tacl_a_00232</identifier>
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        <date>2013</date>
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%0 Journal Article
%T What Makes Writing Great? First Experiments on Article Quality Prediction in the Science Journalism Domain
%A Louis, Annie
%A Nenkova, Ani
%J Transactions of the Association for Computational Linguistics
%D 2013
%V 1
%I MIT Press
%C Cambridge, MA
%F louis-nenkova-2013-makes
%X Great writing is rare and highly admired. Readers seek out articles that are beautifully written, informative and entertaining. Yet information-access technologies lack capabilities for predicting article quality at this level. In this paper we present first experiments on article quality prediction in the science journalism domain. We introduce a corpus of great pieces of science journalism, along with typical articles from the genre. We implement features to capture aspects of great writing, including surprising, visual and emotional content, as well as general features related to discourse organization and sentence structure. We show that the distinction between great and typical articles can be detected fairly accurately, and that the entire spectrum of our features contribute to the distinction.
%R 10.1162/tacl_a_00232
%U https://aclanthology.org/Q13-1028
%U https://doi.org/10.1162/tacl_a_00232
%P 341-352

Markdown (Informal)

[What Makes Writing Great? First Experiments on Article Quality Prediction in the Science Journalism Domain](https://aclanthology.org/Q13-1028) (Louis & Nenkova, TACL 2013)

• What Makes Writing Great? First Experiments on Article Quality Prediction in the Science Journalism Domain (Louis & Nenkova, TACL 2013)

ACL

• Annie Louis and Ani Nenkova. 2013. What Makes Writing Great? First Experiments on Article Quality Prediction in the Science Journalism Domain. Transactions of the Association for Computational Linguistics, 1:341–352.