VLDB 2026 Research / reviewers in the wild / expert
Daniel Fidel
dblp:401/7638
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2025
0009-0007-4109-5826ORCID · 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 |
User interface design and tools · 44% Collaborative and social computing · 44% Accessibility and assistive technology · 13% |
Topics — the 2 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
User interface design and tools › user interface design
dark patterns |
0.9 | 1 | 2025 | A Comparative Study of How People With and Without ADHD Recognise and Avoid Dark Patterns on Social Media · CHI 2025 |
Collaborative and social computing
vulnerable populations |
0.9 | 1 | 2025 | A Comparative Study of How People With and Without ADHD Recognise and Avoid Dark Patterns on Social Media · CHI 2025 |
Methods — techniques the papers use, named apart from their topics
interactive web study · 0.9comparative study · 0.9
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | A Comparative Study of How People With and Without ADHD Recognise and Avoid Dark Patterns on Social MediaabstractDark patterns are deceptive strategies that recent work in humancomputer interaction (HCI) has captured throughout digital domains, including social networking sites (SNSs).While research has identified difficulties among people to recognise dark patterns effectively, few studies consider vulnerable populations and their experience in this regard, including people with attention deficit hyperactivity disorder (ADHD), who may be especially susceptible to attention-grabbing tricks.Based on an interactive web study with 135 participants, we investigate SNS users' ability to recognise and avoid dark patterns by comparing results from participants with and without ADHD.In line with prior work, we noticed overall low recognition of dark patterns with no significant differences between the two groups.Yet, ADHD individuals were able to avoid specific dark patterns more often.Our results advance previous work by understanding dark patterns in a realistic environment and offer insights into their effect on vulnerable populations. Thomas Eßmeyer, Daniel Fidel, Evropi Stefanidi, Pawel W. Wozniak, Rainer Malaka, Jasmin Niess |
CHI | 2 |