Papers by Andrew Piper
BRIGHTER: BRIdging the Gap in Human-Annotated Textual Emotion Recognition Datasets for 28 Languages (2025.acl-long)
Copied to clipboard
Shamsuddeen Hassan Muhammad, Nedjma Ousidhoum, Idris Abdulmumin, Jan Philip Wahle, Terry Ruas, Meriem Beloucif, Christine de Kock, Nirmal Surange, Daniela Teodorescu, Ibrahim Said Ahmad, David Ifeoluwa Adelani, Alham Fikri Aji, Felermino D. M. A. Ali, Ilseyar Alimova, Vladimir Araujo, Nikolay Babakov, Naomi Baes, Ana-Maria Bucur, Andiswa Bukula, Guanqun Cao, Rodrigo Tufiño, Rendi Chevi, Chiamaka Ijeoma Chukwuneke, Alexandra Ciobotaru, Daryna Dementieva, Murja Sani Gadanya, Robert Geislinger, Bela Gipp, Oumaima Hourrane, Oana Ignat, Falalu Ibrahim Lawan, Rooweither Mabuya, Rahmad Mahendra, Vukosi Marivate, Alexander Panchenko, Andrew Piper, Charles Henrique Porto Ferreira, Vitaly Protasov, Samuel Rutunda, Manish Shrivastava, Aura Cristina Udrea, Lilian Diana Awuor Wanzare, Sophie Wu, Florian Valentin Wunderlich, Hanif Muhammad Zhafran, Tianhui Zhang, Yi Zhou, Saif M. Mohammad
| Challenge: | Emotion recognition is an umbrella term for several NLP tasks, but most work on high-resource languages has focused on low-resourced languages. |
| Approach: | They propose to use emotion recognition to describe perceived emotions in 28 different languages and across several domains to identify and annotate the datasets. |
| Outcome: | The proposed datasets cover low-resource languages from Africa, Asia, Eastern Europe, and Latin America, with instances labeled by fluent speakers. |
Fiction Flows: A Replication and Reinterpretation of Narrative Sequentiality (2026.acl-long)
Copied to clipboard
| Challenge: | a new study shows that imagined narratives exhibit higher "flow" than recalled narratives, but this advantage is not reducible to standard coherence measures. |
| Approach: | They propose a language-model-based measure of sentence-level predictability to measure narrative flow . they find that imagined stories flow better than recalled ones . |
| Outcome: | The proposed measure of sentence-level predictability is based on language models . it shows that fiction exhibits a robust sequentiality advantage over reality-bound genres . |
The Empirical Variability of Narrative Perceptions of Social Media Texts (2024.emnlp-main)
Copied to clipboard
| Challenge: | Identifying stories in social media texts provides a lens through which we can study how individuals and communities process and communicate experiences. |
| Approach: | They construct a taxonomy of crowd workers’ varied and nuanced perceptions of storytelling by open-coding their free-text rationales. |
| Outcome: | The proposed model shows that crowd workers disagree on categorical labels, free-text storytelling rationales, authorial intent, and more. |
NarraBench: A Comprehensive Framework for Narrative Benchmarking (2026.eacl-long)
Copied to clipboard
| Challenge: | Existing benchmarks for narrative understanding are poorly aligned with existing metrics. |
| Approach: | They propose to use NarraBench to assess aspects of narrative understanding that are either overlooked in current work or are poorly aligned with existing metrics. |
| Outcome: | The proposed taxonomy and survey are useful to NLP researchers . they find that only 27% of tasks are well captured by existing benchmarks . |
Evaluating Taxonomy Free Character Role Labeling (TF-CRL) in News Stories using Large Language Models (2025.emnlp-main)
Copied to clipboard
| Challenge: | TF-CRL assigns open-ended narrative role labels to characters in news stories based on their functional role in the narrative. |
| Approach: | They propose a task that assigns open-ended narrative role labels to characters in news stories based on their functional role in the narrative. |
| Outcome: | The proposed task outperforms human annotators across dimensions and shows that it is robust to human preference rankings and ratings. |
“Are you kidding me?”: Detecting Unpalatable Questions on Reddit (2021.eacl-main)
Copied to clipboard
| Challenge: | Existing methods to detect online abuse focus on the more explicit forms of abuse . existing methods focus on detecting subtler forms of online abuse leaving them unnoticed . |
| Approach: | They propose a task to detect unpalatable questions using reddit data to implement a context-aware dataset and implement 'learning models' they hope future research will address subtle forms of abuse since harm passes unnoticed through existing detection systems. |
| Outcome: | The proposed task is based on a dataset of reddit users and a conversational context. |
CR4-NarrEmote: An Open Vocabulary Dataset of Narrative Emotions Derived Using Citizen Science (2025.emnlp-main)
Copied to clipboard
| Challenge: | CR4-NarrEmote is a large-scale, open-vocabulary dataset of narrative emotions . authors present a dataset of emotion annotations for novel and novel narratives . |
| Approach: | They introduce a large-scale, open-vocabulary dataset of narrative emotions . they use a citizen science initiative to collect emotion annotations from 43,000 passages . |
| Outcome: | The proposed dataset provides an important foundation for affective computing and narrative understanding. |
Probing Narrative Morals: A New Character-Focused MFT Framework for Use with Large Language Models (2025.emnlp-main)
Copied to clipboard
| Challenge: | Existing methods to categorize moral foundations in storytelling are limited. |
| Approach: | They propose a character-centric method to quantify moral foundations in storytelling using large language models and a novel Moral Foundations Character Action Questionnaire to validate their approach against human annotations. |
| Outcome: | The proposed method validates against human annotations and then applies to 2,697 folktales from 55 countries. |
Social Story Frames: Contextual Reasoning about Narrative Intent and Reception (2026.acl-long)
Copied to clipboard
Joel Mire, Maria Antoniak, Steven R Wilson, Zexin Ma, Achyutarama R Ganti, Andrew Piper, Maarten Sap
| Challenge: | SocialStoryFrames is a formalism for distilling plausible inferences about reader response . authors characterize frequency and interdependence of storytelling intents across communities . |
| Approach: | They propose a formalism for distilling plausible inferences about reader response using conversational context and a taxonomy grounded in narrative theory, linguistic pragmatics, and psychology. |
| Outcome: | The proposed model can be used to analyze reader responses in online communities. |
Where Do People Tell Stories Online? Story Detection Across Online Communities (2024.acl-long)
Copied to clipboard
| Challenge: | 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. |
| Approach: | They propose a toolkit to detect stories in online communities using an annotated reddit dataset and a codebook adapted to social media context. |
| Outcome: | The proposed toolkit includes an annotation-rich dataset of 502 Reddit posts and comments . it also includes a codebook adapted to the social media context and models to predict storytelling at document and span levels. |
Story Morals: Surfacing value-driven narrative schemas using large language models (2024.emnlp-main)
Copied to clipboard
| Challenge: | Using large language models, we extract and validate story morals across a diverse set of narrative genres. |
| Approach: | They propose a task of narrative schema labelling based on the concept of "story morals" they use large language models to extract and validate story morals across a diverse set of genres . |
| Outcome: | The proposed method extracts and validates story morals across folktales, novels, movies and TV, personal stories from social media and the news using automated metrics and human assessments. |
Narrative Theory for Computational Narrative Understanding (2021.emnlp-main)
Copied to clipboard
| Challenge: | a growing body of theoretical work on narrative has been focused on the field of natural language processing . this position paper aims to provide a unifying framework for the computational study of narrative . |
| Approach: | They propose to introduce dominant theoretical frameworks to the NLP community and situate current research within distinct narratological traditions. |
| Outcome: | The proposed framework would allow for new empirical questions and applications in the field of natural language processing. |