Demo Data from SIGIR 2026 / reviewers in the wild / expert
Jui-Ching Kuo
dblp:399/9959
· DBLP profile ↗
2ranked-venue papers
0as first author
2since 2021 · last 2026
0009-0000-0831-4774ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Human-computer interaction and ubiquitous computing · 2 · 2 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
2 papers |
Health and well-being technologies · 88% Human-AI interaction · 12% | |
| Databases, data mining, and information retrieval
1 paper |
Information retrieval · 100% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Health and well-being technologies
digital well-being |
1.0 | 1 | 2026 | Does Longer Phone Use Always Feel Worse? Examining How Intention and Duration Shape Evaluations of Time Use · CHI 2026 |
Health and well-being technologies
personal informatics |
1.0 | 1 | 2026 | Does Longer Phone Use Always Feel Worse? Examining How Intention and Duration Shape Evaluations of Time Use · CHI 2026 |
Information retrieval › user interaction
user feedback |
0.9 | 1 | 2025 | Beyond Explicit and Implicit: How Users Provide Feedback to Shape Personalized Recommendation Content · CHI 2025 |
Human-AI interaction › human-centered AI
user control |
0.3 | 1 | 2025 | Beyond Explicit and Implicit: How Users Provide Feedback to Shape Personalized Recommendation Content · CHI 2025 |
Methods — techniques the papers use, named apart from their topics
screenshot labeling · 1.0experience sampling · 1.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2026 | Does Longer Phone Use Always Feel Worse? Examining How Intention and Duration Shape Evaluations of Time UseabstractPrior work has examined how users judge their smartphone use, typically focusing on either usage duration or intention. How these two factors jointly shape such evaluations remains unclear. We conducted a two-week study with 104 participants, who reviewed their screenshots and provided labels of both usage intention and evaluation of time use. Across 73,000 sessions (6.1M screenshots), the relationship between duration and evaluation was initially linear but then bounded: positive evaluations declined and negative ones rose with longer phone use duration but both eventually stabilized, most often judged neutral. Trajectories varied by intention. Entertainment mirrored the overall trend; functional use continually lost positive evaluations, whereas information-seeking became increasingly positive during the first half hour before later declining; messaging-based connections slowly lost positive evaluations, while social media–based connections declined more quickly; finally, “no specific intention” unfolded in phases—from short positive use to regret-prone mid-length episodes to neutral long sessions. Je-Wei Hsu, Ching-Ting Lin, Uei-Dar Chen, Jui-Ching Kuo, Yi-Hua Tsai, Jui-Chun Liu, Yong-Han Lin, Chen-Ya Chen, Razieh Pourafshari, Mu-Jung Cho, Joseph B. Bayer, Yung-Ju Chang |
CHI | 4 |
| 2025 | Beyond Explicit and Implicit: How Users Provide Feedback to Shape Personalized Recommendation Content
Wenqi Li 0002, Jui-Ching Kuo, Manyu Sheng, Qunfang Wu |
CHI | 2 |