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James Cummings 0002

dblp:34/9068 · also James J. Cummings · DBLP profile ↗
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3ranked-venue papers
1as first author
3since 2021 · last 2025
0000-0001-6239-2634ORCID · verified

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

Human-computer interaction and ubiquitous computing · 3 · 1 first-author · 3 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
Collaborative and social computing · 87% Immersive interaction · 13%
Network and information security
1 paper
Privacy and data protection · 100%

Topics — the 3 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Collaborative and social computing › interpersonal communication
self-disclosure
0.912025
Self-Disclosure in Social Virtual Reality: The Influence of Information Management Dynamics, Social Presence, and Privacy Concerns · CHI 2025
Collaborative and social computing › collaborative virtual environments
social virtual reality
0.912025
Self-Disclosure in Social Virtual Reality: The Influence of Information Management Dynamics, Social Presence, and Privacy Concerns · CHI 2025
Immersive interaction › virtual reality › presence
social presence in VR
0.312025
Self-Disclosure in Social Virtual Reality: The Influence of Information Management Dynamics, Social Presence, and Privacy Concerns · CHI 2025

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

survey study · 1.7
YearPublicationVenuePosition
2025 Self-Disclosure in Social Virtual Reality: The Influence of Information Management Dynamics, Social Presence, and Privacy Concerns
abstract
Peer Reviewed
James Cummings 0002, Alexis Shore, Yihan Danny Jia
CHI1
2023 An Exploratory Analysis of Interface Features Influencing Mobile Location Data Disclosure
abstract
Mobile location based services (LBS) often ask users to consent to over disclose location data in exchange for their service. This online experiment manipulated interface features within an LBS consent screen to understand their independent and interactive influence on location data obscurity decisions. Participants (N = 502) were led to believe they were involved in a location-tracking study, allowing for revealed preferences in their decisions. Results indicate that social proof and willingness-to-accept framing positively influenced participants’ likelihood to obscure their location data. While the presence of friction and defaults had no direct effect, both interacted with other interface features in influencing decision-making.
Alexis Shore, James Cummings 0002
Int. J. Hum. Comput. Interact.2
2021 Screenomics: A Framework to Capture and Analyze Personal Life Experiences and the Ways that Technology Shapes Them
abstract
Digital experiences capture an increasingly large part of life, making them a preferred, if not required, method to describe and theorize about human behavior. Digital media also shape behavior by enabling people to switch between different content easily, and create unique threads of experiences that pass quickly through numerous information categories. Current methods of recording digital experiences provide only partial reconstructions of digital lives that weave - often within seconds - among multiple applications, locations, functions and media. We describe an end-to-end system for capturing and analyzing the "screenome" of life in media, i.e., the record of individual experiences represented as a sequence of screens that people view and interact with over time. The system includes software that collects screenshots, extracts text and images, and allows searching of a screenshot database. We discuss how the system can be used to elaborate current theories about psychological processing of technology, and suggest new theoretical questions that are enabled by multiple time scale analyses. Capabilities of the system are highlighted with eight research examples that analyze screens from adults who have generated data within the system. We end with a discussion of future uses, limitations, theory and privacy.
Byron Reeves, Nilam Ram, Thomas N. Robinson, James Cummings 0002, C. Lee Giles, Jennifer Pan, Agnese Chiatti, Mj Cho, Katie Roehrick, Xiao Yang 0010, Anupriya Gagneja, Miriam Brinberg, Daniel Muise, Yingdan Lu, Mufan Luo, Andrew Fitzgerald, Leo Yeykelis
Hum. Comput. Interact.4