Demo Data from SIGIR 2026 / reviewers in the wild / expert
Danielle Unéus
dblp:433/0011
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2026
0009-0000-5771-7641ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Human-computer interaction and ubiquitous computing · 1 · 1 since 2021
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Human-computer interaction and pervasive computing
1 paper |
Health and well-being technologies · 77% Design research and methods · 23% |
Topics — the 1 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Design research and methods › qualitative analysis
reflexive thematic analysis |
0.3 | 1 | 2026 | "Chasing Shadows": Understanding Personal Data Externalization and Self-Tracking for Neurodivergent Individuals · CHI 2026 |
Methods — techniques the papers use, named apart from their topics
workshop · 1.0reflexive thematic analysis · 1.0qualitative study · 1.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2026 | "Chasing Shadows": Understanding Personal Data Externalization and Self-Tracking for Neurodivergent IndividualsabstractWe examine how neurodivergent individuals experience creating, interacting with, and reflecting on personal data about masking. Although self-tracking is often framed as enabling self-insight, this is rarely our experience as neurodivergent individuals and researchers. To better understand this disconnect, we conducted a two-phase qualitative study. First, a workshop where six participants with autism and/or ADHD crafted visual representations of masking experiences. Then, three participants continued by designing and using personalized self-tracking focused on unmasking over two weeks. Using reflexive thematic analysis of activities and interviews, we find that self-tracking imposes substantial interpretive and emotional demands, shaped by context-dependencies that challenge assumptions in self-tracking. We also find that facilitated sharing of experiences might validate emotional responses and support reflection. We identify three emotional dimensions that shape engagement with personal data in a working model of emotion in self-tracking, and discuss implications for designing self-tracking and reflective practices that incorporate peer support and better account for context and emotional labor. Tanya Rudberg Selin, Danielle Unéus, Søren Knudsen |
CHI | 2 |