Demo Data from EDBT 2026 / reviewers in the wild / expert
Mieke Boon
dblp:289/4659
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2021
0000-0003-2492-2854ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1 · 1 since 2021Human-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 |
Human-robot interaction · 100% |
Topics — the 3 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Human-robot interaction
humanlikeness |
0.5 | 1 | 2021 | Uncanny, Sexy, and Threatening Robots: The Online Community's Attitude to and Perceptions of Robots Varying in Humanlikeness and Gender · HRI 2021 |
Human-robot interaction › anthropomorphism
robot appearance |
0.5 | 1 | 2021 | Uncanny, Sexy, and Threatening Robots: The Online Community's Attitude to and Perceptions of Robots Varying in Humanlikeness and Gender · HRI 2021 |
Human-robot interaction › anthropomorphism
uncanny valley |
0.5 | 1 | 2021 | Uncanny, Sexy, and Threatening Robots: The Online Community's Attitude to and Perceptions of Robots Varying in Humanlikeness and Gender · HRI 2021 |
Methods — techniques the papers use, named apart from their topics
content analysis · 0.5
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2021 | Uncanny, Sexy, and Threatening Robots: The Online Community's Attitude to and Perceptions of Robots Varying in Humanlikeness and GenderabstractTo get a better understanding of people's natural responses to humanlike robots outside the lab, we analyzed commentary on online videos depicting robots of different humanlikeness and gender. We built on previous work, which compared online video commentary of moderately and highly humanlike robots with respect to valence, uncanny valley, threats, and objectification. Additionally, we took into account the robot's gender, its appearance, its societal impact, the attribution of mental states, and how people attribute human stereotypes to robots. The results are mostly in line with previous work. Overall, the findings indicate that moderately humanlike robot design may be preferable over highly humanlike robot design because it is less associated with negative attitudes and perceptions. Robot designers should therefore be cautious when designing highly humanlike and gendered robots. Quirien R. M. Hover, Ella Velner, Thomas Beelen, Mieke Boon, Khiet P. Truong |
HRI | 4 |