Micro-narratives: A Scalable Method for Eliciting Stories of People’s Lived Experience

Engaging with people's lived experiences is foundational for HCI research and design. This paper introduces a novel narrative elicitation method to empower people to easily articulate 'micro-narratives' emerging from their lived experiences, irrespective of their writing ability or background. Our approach aims to enable at-scale collection of rich, co-created datasets that highlight target populations' voices with minimal participant burden, while precisely addressing specific research questions. To pilot this idea, and test its feasibility, we: (i) developed an AI-powered prototype, which leverages LLM-chaining to scaffold the cognitive steps necessary for users' narrative articulation; (ii) deployed it in three mixed-methods studies involving over 380 users; and (iii) consulted with established academics as well as C-level staff at (inter)national non-profits to map out potential applications. Both qualitative and quantitative findings show the acceptability and promise of the micro-narrative method, while also identifying the ethical and safeguarding considerations necessary for any at-scale deployments.

Authors

Institutions

Publication Details

Published
2025-04-24
DOI
https://doi.org/10.1145/3706598.3713999
Citations
2
Primary Topic
Innovative Human-Technology Interaction
Type
article
Field-Weighted Citation Impact
3.87

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Micro-narratives: A Scalable Method for Eliciting Stories of People’s Lived Experience

Predrag Klasnja, Amy Orben, Petr Slovák, Seray Ibrahim et al.
2 citations
Innovative Human-Technology Interaction
3.87
article

Micro-narratives: A Scalable Method for Eliciting Stories of People’s Lived Experience

Predrag Klasnja, Amy Orben, Petr Slovák, Seray Ibrahim, James J. Gross, Sean A. Munson, C. Aubrey Rhodes, Ashish Mehta, Amira Skeggs, Valerie Yap
article en
2 citations

Abstract

Engaging with people's lived experiences is foundational for HCI research and design. This paper introduces a novel narrative elicitation method to empower people to easily articulate 'micro-narratives' emerging from their lived experiences, irrespective of their writing ability or background. Our approach aims to enable at-scale collection of rich, co-created datasets that highlight target populations' voices with minimal participant burden, while precisely addressing specific research questions. To pilot this idea, and test its feasibility, we: (i) developed an AI-powered prototype, which leverages LLM-chaining to scaffold the cognitive steps necessary for users' narrative articulation; (ii) deployed it in three mixed-methods studies involving over 380 users; and (iii) consulted with established academics as well as C-level staff at (inter)national non-profits to map out potential applications. Both qualitative and quantitative findings show the acceptability and promise of the micro-narrative method, while also identifying the ethical and safeguarding considerations necessary for any at-scale deployments.

Vol. 2025
King's College London (GB), MRC Cognition and Brain Sciences Unit (GB), University of Washington (US), University of Cambridge (GB), University of Michigan (US), Stanford University (US)
UK Research and Innovation, Jacobs Foundation, Medical Research Council
Reduced inequalities
Openalex Percentile: Top 8%
Innovative Human-Technology Interaction
3.87
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.