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Andrew Piper

8 accepted papers

2025

BRIGHTER: BRIdging the Gap in Human-Annotated Textual Emotion Recognition Datasets for 28 Languages

Shamsuddeen Hassan Muhammad, Nedjma Ousidhoum, Idris Abdulmumin, Jan Philip Wahle, Terry Ruas, Meriem Beloucif +42
ACL 2025long

People worldwide use language in subtle and complex ways to express emotions. Although emotion recognition–an umbrella term for several NLP tasks–impacts various applications within NLP and beyond, most work in this area has focused on high-resource languages. This has led to significant disparities…

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2025

CR4-NarrEmote: An Open Vocabulary Dataset of Narrative Emotions Derived Using Citizen Science

Andrew Piper, Robert Budac
EMNLP 2025

We introduce “Citizen Readers for Narrative Emotions” (CR4-NarrEmote), a large-scale, open-vocabulary dataset of narrative emotions derived through a citizen science initiative. Over a four-month period, 3,738 volunteers contributed more than 200,000 emotion annotations across 43,000 passages from l

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2025

Evaluating Taxonomy Free Character Role Labeling (TF-CRL) in News Stories using Large Language Models

David G Hobson, Derek Ruths, Andrew Piper
EMNLP 2025

We introduce Taxonomy-Free Character Role Labeling (TF-CRL); a novel task that assigns open-ended narrative role labels to characters in news stories based on their functional role in the narrative. Unlike fixed taxonomies, TF-CRL enables more nuanced and comparative analysis by generating compositi

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2025

Probing Narrative Morals: A New Character-Focused MFT Framework for Use with Large Language Models

Luca Mitran, Sophie Wu, Andrew Piper
EMNLP 2025

Moral Foundations Theory (MFT) provides a framework for categorizing different forms of moral reasoning, but its application to computational narrative analysis remains limited. We propose a novel character-centric method to quantify moral foundations in storytelling, using large language models (LL

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2024

Story Morals: Surfacing value-driven narrative schemas using large language models

David G Hobson, Haiqi Zhou, Derek Ruths, Andrew Piper
EMNLP 2024main

Stories are not only designed to entertain but encode lessons reflecting their authors’ beliefs about the world. In this paper, we propose a new task of narrative schema labelling based on the concept of “story morals” to identify the values and lessons conveyed in stories. Using large language mode…

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2024

The Empirical Variability of Narrative Perceptions of Social Media Texts

Joel Mire, Maria Antoniak, Elliott Ash, Andrew Piper, Maarten Sap
EMNLP 2024main

Most NLP work on narrative detection has focused on prescriptive definitions of stories crafted by researchers, leaving open the questions: how do crowd workers perceive texts to be a story, and why? We investigate this by building StoryPerceptions, a dataset of 2,496 perceptions of storytelling in…

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2024

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

Maria Antoniak, Joel Mire, Maarten Sap, Elliott Ash, Andrew Piper
ACL 2024long

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 pos…

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