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Kyle Essenmacher

dblp:292/5645 · DBLP profile ↗
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2ranked-venue papers
0as first author
2since 2021 · last 2021
—ORCID · none

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

Human-computer interaction and ubiquitous computing · 2 · 2 since 2021Artificial intelligence and machine learning · 1 · 1 since 2021Applied, interdisciplinary, general and emerging 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 · 44% Usability and user experience research · 44% Collaborative and social computing · 13%

Topics — the 2 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Human-robot interaction
robot acceptance
0.512021
A Meta-Analysis of Human Personality and Robot Acceptance in Human-Robot Interaction · CHI 2021
Usability and user experience research
technology acceptance
0.512021
A Meta-Analysis of Human Personality and Robot Acceptance in Human-Robot Interaction · CHI 2021

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

meta-analysis · 0.5
YearPublicationVenuePosition
2021 A Meta-Analysis of Human Personality and Robot Acceptance in Human-Robot Interaction
abstract
Human personality has been identified as a predictor of robot acceptance in the human–robot interaction (HRI) literature. Despite this, the HRI literature has provided mixed support for this assertion. To better understand the relationship between human personality and robot acceptance, this paper conducts a meta-analysis of 26 studies. Results found a positive relationship between human personality and robot acceptance. However, this relationship varied greatly by the specific personality trait along with the study sample’s age, gender diversity, task, and global region. This meta-analysis also identified gaps in the literature. Namely, additional studies are needed that investigate both the big five personality traits and other personality traits, examine a more diverse age range, and utilize samples from previously unexamined regions of the globe.
Connor Esterwood, Kyle Essenmacher, Fanpan Zeng, Lionel P. Robert Jr.
CHI2
2021 Birds of a Feather Flock Together: But do Humans and Robots? A Meta-Analysis of Human and Robot Personality Matching
abstract
Collaborative work between humans and robots holds great potential but, such potential is diminished should humans fail to accept robots as collaborators. One solution is to design robots to have a similar personality to their human collaborators. Typically, this is done by matching the human’s and robot’s personality using one or more of the Big Five Personality (BFI) traits. The results of this matching, however, have been mixed. This makes it difficult to know whether personality similarity promotes robot acceptance. To address this shortcoming, we conducted a systematic quantitative meta- analysis of 13 studies. Overall, the results support the assertion that matching personalities between humans and robots promotes robot acceptance.
Connor Esterwood, Kyle Essenmacher, Fanpan Zeng, Lionel P. Robert Jr.
RO-MAN2