Demo Data from SIGIR 2026 / reviewers in the wild / expert
Heidy C. Maldonado
dblp:09/4419
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2008
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1Human-computer interaction and ubiquitous computing · 1
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% Collaborative and social computing · 44% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Collaborative and social computing › computer-mediated communication
cultural differences |
0.1 | 1 | 2008 | Relational vs. group self-construal: untangling the role of national culture in HRI · HRI 2008 |
Human-robot interaction
social robot |
0.1 | 1 | 2008 | Relational vs. group self-construal: untangling the role of national culture in HRI · HRI 2008 |
Human-robot interaction
trust in robots |
0.0 | 1 | 2008 | Relational vs. group self-construal: untangling the role of national culture in HRI · HRI 2008 |
Methods — techniques the papers use, named apart from their topics
2x2x2 experiment · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2008 | Relational vs. group self-construal: untangling the role of national culture in HRIabstractAs robots (and other technologies) increasingly make decisions on behalf of people, it is important to understand how people from diverse cultures respond to this capability. Thus far, much design of autonomous systems takes a Western view valuing individual preferences and choice. We challenge the assumption that Western values are universally optimal for robots. In this study, we sought to clarify the effects of users' cultural background on human-robot collaboration by investigating their attitudes toward and the extent to which people accepted choices made by a robot or human assistant. A 2x2x2 experiment was conducted with nationality (US vs. Chinese), in group strength (weak vs. strong) and human vs. robot assistant as dimensions. US participants reported higher trust of and compliance with the assistants (human and robot) although when the assistant was characterized as a strong ingroup member, Chinese as compared with the US subjects were more comfortable. Chinese also reported a stronger sense of control with both assistants and were more likely to anthropomorphize the robot than were US subjects. This pattern of findings confirms that people from different national cultures may respond differently to robots, but also suggests that predictions from human-human interaction do not hold universally. Vanessa Evers, Heidy C. Maldonado, Talia L. Brodecki, Pamela J. Hinds |
HRI | 2 |