Where Do People Tell Stories Online? Story Detection Across Online Communities

Maria Antoniak, Joel Mire, Maarten Sap, Elliott Ash, Andrew Piper


Abstract
Story detection in online communities is a challenging task as stories are scattered across communities and interwoven with non-storytelling spans within a single text. We address this challenge by building and releasing the StorySeeker toolkit, including a richly annotated dataset of 502 Reddit posts and comments, a detailed codebook adapted to the social media context, and models to predict storytelling at the document and span levels. Our dataset is sampled from hundreds of popular English-language Reddit communities ranging across 33 topic categories, and it contains fine-grained expert annotations, including binary story labels, story spans, and event spans. We evaluate a range of detection methods using our data, and we identify the distinctive textual features of online storytelling, focusing on storytelling spans, which we introduce as a new task. We illuminate distributional characteristics of storytelling on a large community-centric social media platform, and we also conduct a case study on r/ChangeMyView, where storytelling is used as one of many persuasive strategies, illustrating that our data and models can be used for both inter- and intra-community research. Finally, we discuss implications of our tools and analyses for narratology and the study of online communities.
Anthology ID:
2024.acl-long.383
Volume:
Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Month:
August
Year:
2024
Address:
Bangkok, Thailand
Editors:
Lun-Wei Ku, Andre Martins, Vivek Srikumar
Venue:
ACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
7104–7130
Language:
URL:
https://aclanthology.org/2024.acl-long.383
DOI:
10.18653/v1/2024.acl-long.383
Bibkey:
Cite (ACL):
Maria Antoniak, Joel Mire, Maarten Sap, Elliott Ash, and Andrew Piper. 2024. Where Do People Tell Stories Online? Story Detection Across Online Communities. In Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 7104–7130, Bangkok, Thailand. Association for Computational Linguistics.
Cite (Informal):
Where Do People Tell Stories Online? Story Detection Across Online Communities (Antoniak et al., ACL 2024)
Copy Citation:
PDF:
https://preview.aclanthology.org/dois-2013-emnlp/2024.acl-long.383.pdf