Demo Data from EDBT 2026 / reviewers in the wild / expert
Evan Metsky
dblp:161/3427
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2015
—ORCID · none
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 · 77% Human-AI interaction · 23% | |
| Interdisciplinary, comprehensive, and emerging computing
1 paper |
Computational social science and digital humanities · 100% |
Topics — the 2 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Computational social science and digital humanities
future of work |
0.2 | 1 | 2015 | Working with Machines: The Impact of Algorithmic and Data-Driven Management on Human Workers · CHI 2015 |
Collaborative and social computing › socio-technical systems
algorithmic management |
0.2 | 1 | 2015 | Working with Machines: The Impact of Algorithmic and Data-Driven Management on Human Workers · CHI 2015 |
Methods — techniques the papers use, named apart from their topics
thematic analysis · 0.4qualitative study · 0.4
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2015 | Working with Machines: The Impact of Algorithmic and Data-Driven Management on Human WorkersabstractSoftware algorithms are changing how people work in an ever-growing number of fields, managing distributed human workers at a large scale. In these work settings, human jobs are assigned, optimized, and evaluated through algorithms and tracked data. We explore the impact of this algorithmic, data-driven management on human workers and work practices in the context of Uber and Lyft, new ridesharing services. Our findings from a qualitative study describe how drivers responded when algorithms assigned work, provided informational support, and evaluated their performance, and how drivers used online forums to socially make sense of the algorithm features. Implications and future work are discussed. Min Kyung Lee, Daniel Kusbit, Evan Metsky, Laura A. Dabbish |
CHI | 3 |