Demonstration venue · read-only. Every page can be browsed; the buttons that would change it are switched off. Create an account to run TaxoReview on your own data. A simulation from public publication records: the people listed were not invited and did not agree to review.
? Tutorial for this page

Eli Reber

dblp:258/4987 · DBLP profile ↗
← Back
1ranked-venue papers
0as first author
0since 2021 · last 2020
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1Systems, architecture and hardware · 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 · 77% Collaborative and social computing · 23%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Human-robot interaction › social robot
group interaction with robots
0.412020
Can I Trust You? A User Study of Robot Mediation of a Support Group · ICRA 2020
Human-robot interaction › assistive robotics
socially assistive robotics
0.412020
Can I Trust You? A User Study of Robot Mediation of a Support Group · ICRA 2020
Collaborative and social computing › social interaction
group dynamics
0.112020
Can I Trust You? A User Study of Robot Mediation of a Support Group · ICRA 2020
Collaborative and social computing › computer-mediated communication
interpersonal trust
0.112020
Can I Trust You? A User Study of Robot Mediation of a Support Group · ICRA 2020

Methods — techniques the papers use, named apart from their topics

user study · 0.4dyadic trust scale · 0.4
YearPublicationVenuePosition
2020 Can I Trust You? A User Study of Robot Mediation of a Support Group
abstract
Socially assistive robots have the potential to improve group dynamics when interacting with groups of people in social settings. This work contributes to the understanding of those dynamics through a user study of trust dynamics in the novel context of a robot mediated support group. For this study, a novel framework for robot mediation of a support group was developed and validated. To evaluate interpersonal trust in the multi-party setting, a dyadic trust scale was implemented and found to be uni-factorial, validating it as an appropriate measure of general trust. The results of this study demonstrate a significant increase in average interpersonal trust after the group interaction session, and qualitative post-session interview data report that participants found the interaction helpful and successfully supported and learned from one other. The results of the study validate that a robot-mediated support group can improve trust among strangers and allow them to share and receive support for their academic stress.
Chris Birmingham, Zijian Hu 0001, Kartik Mahajan, Eli Reber, Maja J. Mataric
ICRA4