Demo Data from EDBT 2026 / reviewers in the wild / expert
Priyanka Senapati
dblp:316/5743
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2022
—ORCID · none
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 · 81% Collaborative and social computing · 19% |
Topics — the 2 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Human-robot interaction
entitativity |
0.2 | 1 | 2022 | You Had Me at Hello: The Impact of Robot Group Presentation Strategies on Mental Model Formation · HRI 2022 |
Collaborative and social computing › social interaction
group dynamics |
0.2 | 1 | 2022 | You Had Me at Hello: The Impact of Robot Group Presentation Strategies on Mental Model Formation · HRI 2022 |
Methods — techniques the papers use, named apart from their topics
qualitative analysis · 0.6grounded theory · 0.6empirical study · 0.6
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2022 | You Had Me at Hello: The Impact of Robot Group Presentation Strategies on Mental Model FormationabstractResearch has shown how the connections between robots' minds, bodies, and identities can be configured and performed in a variety of ways. In this work, we consider group identity observables: the set of design cues that robot groups use to perform different identity configurations. We explore how group identity observables lead observers to develop different mental models of robot groups. Specifically, we make four key contributions: (1) we define, conceptualize, and taxonomize group identity observables; (2) we use Grounded Theory-informed analysis of qualitative data to produce a taxonomy of users' mental models invoked by variation in those observables; (3) we empirically demonstrate (n=166) how variations in observables lead to different mental models; and (4) we further demonstrate how variations in those observables, and the mental models they evoke, influence key group dynamics constructs like entitativity. Alexandra Bejarano, Samantha Reig, Priyanka Senapati, Tom Williams 0001 |
HRI | 3 |