Demo Data from SIGIR 2026 / reviewers in the wild / expert
Jacqueline N. Lane
dblp:239/7865
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2019
—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% | |
| Software engineering, system software, and programming languages
1 paper |
Empirical software engineering · 100% | |
| Databases, data mining, and information retrieval
1 paper |
Recommender systems · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Collaborative and social computing
team formation |
0.4 | 1 | 2019 | Who Would You Like to Work With? · CHI 2019 |
Empirical software engineering
developer studies |
0.4 | 1 | 2019 | Who Would You Like to Work With? · CHI 2019 |
Recommender systems › group recommendation
teammate recommendation |
0.1 | 1 | 2019 | Who Would You Like to Work With? · CHI 2019 |
Methods — techniques the papers use, named apart from their topics
field study · 1.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2019 | Who Would You Like to Work With?abstractPeople and organizations are increasingly using online platforms to assemble teams. In response, HCI researchers have theorized frameworks and created systems to support team assembly. However, little is known about how users search for and choose teammates on these platforms. We conducted a field study where 530 participants used a team formation system to assemble project teams. We describe how users' traits and social networks influence their teammate searches, teammate choices, and team composition. Our results show that (a) what users initially search for differs from what they finally choose: initially they search for experts and sociable users, but they are ultimately more likely to choose their prior social connections as their teammates; (b) users' decisions lead to non-diverse and segregated teams, where most of the expertise and social capital are concentrated in a few teams. We discuss the implications of these results for designing team formation systems than promote users' agency. Diego Gómez-Zará, Matthew Paras, Marlon Twyman, Jacqueline N. Lane, Leslie A. DeChurch, Noshir S. Contractor |
CHI | 4 |