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        <title>Using Functional Schemas to Understand Social Media Narratives</title>
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        <namePart type="given">Xinru</namePart>
        <namePart type="family">Yan</namePart>
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    <name type="personal">
        <namePart type="given">Aakanksha</namePart>
        <namePart type="family">Naik</namePart>
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    <name type="personal">
        <namePart type="given">Yohan</namePart>
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    <name type="personal">
        <namePart type="given">Carolyn</namePart>
        <namePart type="family">Rose</namePart>
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            <title>Proceedings of the Second Workshop on Storytelling</title>
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            <namePart type="given">Francis</namePart>
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            <namePart type="given">Ting-Hao</namePart>
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            <namePart type="family">Huang</namePart>
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            <namePart type="given">Margaret</namePart>
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    <abstract>We propose a novel take on understanding narratives in social media, focusing on learning ”functional story schemas”, which consist of sets of stereotypical functional structures. We develop an unsupervised pipeline to extract schemas and apply our method to Reddit posts to detect schematic structures that are characteristic of different subreddits. We validate our schemas through human interpretation and evaluate their utility via a text classification task. Our experiments show that extracted schemas capture distinctive structural patterns in different subreddits, improving classification performance of several models by 2.4% on average. We also observe that these schemas serve as lenses that reveal community norms.</abstract>
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    <identifier type="doi">10.18653/v1/W19-3403</identifier>
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        <date>2019-08</date>
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%0 Conference Proceedings
%T Using Functional Schemas to Understand Social Media Narratives
%A Yan, Xinru
%A Naik, Aakanksha
%A Jo, Yohan
%A Rose, Carolyn
%Y Ferraro, Francis
%Y Huang, Ting-Hao ‘Kenneth’
%Y Lukin, Stephanie M.
%Y Mitchell, Margaret
%S Proceedings of the Second Workshop on Storytelling
%D 2019
%8 August
%I Association for Computational Linguistics
%C Florence, Italy
%F yan-etal-2019-using
%X We propose a novel take on understanding narratives in social media, focusing on learning ”functional story schemas”, which consist of sets of stereotypical functional structures. We develop an unsupervised pipeline to extract schemas and apply our method to Reddit posts to detect schematic structures that are characteristic of different subreddits. We validate our schemas through human interpretation and evaluate their utility via a text classification task. Our experiments show that extracted schemas capture distinctive structural patterns in different subreddits, improving classification performance of several models by 2.4% on average. We also observe that these schemas serve as lenses that reveal community norms.
%R 10.18653/v1/W19-3403
%U https://aclanthology.org/W19-3403
%U https://doi.org/10.18653/v1/W19-3403
%P 22-33

Markdown (Informal)

[Using Functional Schemas to Understand Social Media Narratives](https://aclanthology.org/W19-3403) (Yan et al., Story-NLP 2019)

• Using Functional Schemas to Understand Social Media Narratives (Yan et al., Story-NLP 2019)

ACL

• Xinru Yan, Aakanksha Naik, Yohan Jo, and Carolyn Rose. 2019. Using Functional Schemas to Understand Social Media Narratives. In Proceedings of the Second Workshop on Storytelling, pages 22–33, Florence, Italy. Association for Computational Linguistics.