Demo Data from EDBT 2026 / reviewers in the wild / expert
Ishani Aggarwal
dblp:161/3211
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2015
—ORCID · unresolved
Domains — the database's venue-derived domains; a paper can count in several
Human-computer interaction and ubiquitous computing · 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 |
Collaborative and social computing · 100% |
Topics — the 2 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Collaborative and social computing
collective intelligence |
0.2 | 1 | 2015 | Collective Intelligence in Computer-Mediated Collaboration Emerges in Different Contexts and Cultures · CHI 2015 |
Collaborative and social computing › computer-mediated communication
computer-mediated collaboration |
0.2 | 1 | 2015 | Collective Intelligence in Computer-Mediated Collaboration Emerges in Different Contexts and Cultures · CHI 2015 |
Methods — techniques the papers use, named apart from their topics
standardized online battery · 0.2cross-cultural study · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2015 | Collective Intelligence in Computer-Mediated Collaboration Emerges in Different Contexts and CulturesabstractCollective intelligence (CI) is a property of groups that emerges from the coordination and collaboration of members and predicts group performance on a wide range of tasks. Previous studies of CI have been conducted with lab-based groups in the USA. We introduce a new standardized online battery to measure CI and demonstrate consistent emergence of a CI factor across three different studies despite broad differences in (a) communication media (face-to-face vs online), (b) group contexts (short-term ad hoc groups vs long-term groups) and (c) cultural settings (US, Germany, and Japan). In two of the studies, we also show that CI is correlated with a group's performance on more complex tasks. Consequently, the CI metric provides a generalizable performance measure for groups that is robust to broad changes in media, context, and culture, making it useful for testing the effects of general-purpose collaboration technologies intended to improve group performance. David Engel, Anita Williams Woolley, Ishani Aggarwal, Christopher F. Chabris, Masamichi Takahashi, Keiichi Nemoto, Carolin Kaiser, Young Ji Kim, Thomas W. Malone |
CHI | 3 |