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Daniel Halpern 0001

dblp:83/5135-1 · also Daniel Halpern Jelin · DBLP profile ↗
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3ranked-venue papers
1as first author
0since 2021 · last 2016
0000-0002-1569-9876ORCID · verified

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

Human-computer interaction and ubiquitous computing · 2 · 1 first-authorArtificial intelligence and machine learning · 1 · 1 first-authorDatabases, data management, data science and information retrieval · 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% Usability and user experience research · 23%

Topics — the 1 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Human-robot interaction
attitudes toward robots
0.112012
Unveiling robotophobia and cyber-dystopianism: the role of gender, technology and religion on attitudes towards robots · HRI 2012

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

survey · 0.1statistical analysis · 0.1
YearPublicationVenuePosition
2016 Blocked: When the information is hidden by the visualization
abstract
This study investigated how people comprehend three‐dimensional (3D) visualizations and what properties of such visualizations affect comprehension. Participants were asked to draw the face of a 3D visualization after it was cut in half. We videotaped the participants as they drew, erased, verbalized their thoughts, gestured, and moved about a two‐dimensional paper presentation of the 3D visualization. The videorecords were analyzed using a grounded theory approach to generate hypotheses related to comprehension difficulties and visualization properties. Our analysis of the results uncovered three properties that made problem solving more difficult for participants. These were: (a) cuts that were at an angle in relation to at least one plane of reference, (b) nonplanar properties of the features contained in the 3D visualizations including curved layers and v‐shaped layers, and (c) mixed combinations of layers. In contrast, (a) cutting planes that were perpendicular or parallel to the 3D visualization diagram's planes of reference, (b) internal features that were flat/planar, and (c) homogeneous layers were easier to comprehend. This research has direct implications for the generation and use of 3D information visualizations in that it suggests design features to include and avoid.
Kyong Eun Oh, Daniel Halpern 0001, Marilyn Tremaine, James Chiang, Deborah Silver, Karen Bemis
J. Assoc. Inf. Sci. Technol.2
2014 Attitudes towards robots suitability for various jobs as affected robot appearance
abstract
An opinion survey of 878 college students examined attitudes about the suitability of robots for various occupations in society and how these attitudes varied by the robots’ appearance. Factor analyses revealed three primary attitudes: Robot-Liking, Robotphobia and Cyber-Dystopianism, and three occupational niches: social-companionship, surveillance and personal assistants. Attitudes varied depending on subjects’ gender, religion, perceived competence with technologies and engagement with virtual reality environments and avatars. The analysis of relationships between subjects’ attitudes and perception of suitable occupations indicated that Robot-Liking is positively related with social companionship and surveillance occupations, whereas Robotphobia is negatively correlated with the three occupational niches.
James E. Katz, Daniel Halpern 0001
Behav. Inf. Technol.2
2012 Unveiling robotophobia and cyber-dystopianism: the role of gender, technology and religion on attitudes towards robots
abstract
A survey of 873 undergraduate students was conducted to understand which individual factors affect subjects' attitudes toward robots. A third of participants (N=284) were exposed to a humanoid robot, another third (N=293) to a doggy robot, and the remaining third (N=296) to an android. Results showed that in the humanoid condition individuals recognize more humanlike characteristics in robots than in the other two conditions. However humanoid appearance did not affect participants' attitudes toward robots, as others predictors recognized by previous research indicate, such as gender, religion, and perceived competence with information and communication technologies (ICT).
Daniel Halpern 0001, James E. Katz
HRI1