Demo Data from SIGIR 2026 / reviewers in the wild / expert
Ali Momen
dblp:216/5613
· DBLP profile ↗
1ranked-venue papers
1as first author
1since 2021 · last 2022
—ORCID · unresolved
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1 · 1 first-author · 1 since 2021Human-computer interaction and ubiquitous computing · 1 · 1 first-author · 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 · 56% Usability and user experience research · 44% |
Topics — the 2 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Human-robot interaction › robot perception
robot face perception |
0.6 | 1 | 2022 | The Inversion Effect as a Measure of Social Acceptance of Robots · HRI 2022 |
Usability and user experience research › user perception
social acceptability |
0.6 | 1 | 2022 | The Inversion Effect as a Measure of Social Acceptance of Robots · HRI 2022 |
Methods — techniques the papers use, named apart from their topics
user study · 0.6inversion task · 0.6
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2022 | The Inversion Effect as a Measure of Social Acceptance of RobotsabstractIf robots could engage face-processing they would increase the likelihood they are accepted as social companions. However, research has not examined whether and when robot “faces” engage face-processing. The current study examined whether facial-width-to-height ratio (FWHR) modulated face-processing with robots using the “inversion task”-a commonly utilized measure of face perception that leverages the finding that inverting face stimuli hurts recognition performance (i.e., inversion effects) compared to other types of stimuli. We predicted that recognition performance would be more effected by inversion when robots had a low rather than high FWHR. While our statistical results were not significant, descriptive results trended in favor of our hypothesis, demonstrating robots with a lower FHWR had larger inversion effects than robot with a higher FWHR. While more research will be needed to clarify these results, the inversion task is a potentially useful tool to measure the social acceptance of robots through the detection of facial processing. Ali Momen, Eva Wiese |
HRI | 1 |