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Grace A. Benefield

dblp:176/4119 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 2016
—ORCID · none

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

Human-computer interaction and ubiquitous computing · 1 · 1 first-author

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%
Databases, data mining, and information retrieval
1 paper
Web and social media mining · 100%

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

TopicWeightPapersLastEvidence papers
Collaborative and social computing
social capital
0.212016
Virtual Team Networks: How Group Social Capital Affects Team Success in a Massively Multiplayer Online Game · CSCW 2016
Collaborative and social computing › team collaboration
virtual teams
0.212016
Virtual Team Networks: How Group Social Capital Affects Team Success in a Massively Multiplayer Online Game · CSCW 2016
Web and social media mining
social network analysis
0.112016
Virtual Team Networks: How Group Social Capital Affects Team Success in a Massively Multiplayer Online Game · CSCW 2016
Collaborative and social computing
team performance
0.112016
Virtual Team Networks: How Group Social Capital Affects Team Success in a Massively Multiplayer Online Game · CSCW 2016

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

network analysis · 0.5log data analysis · 0.5
YearPublicationVenuePosition
2016 Virtual Team Networks: How Group Social Capital Affects Team Success in a Massively Multiplayer Online Game
abstract
Virtual teams have become a ubiquitous form of organizing, but the impact of social structures within and between teams on group performance remains understudied. This paper uses the case study of a massively multiplayer online game and server log data from over 10,000 players to examine the connection between group social capital (operationalized through guild network structure measures) and team effectiveness, given a variety of in-game social networks. Three different networks, social, task, and exchange networks, are compared and contrasted while controlling for group size, group age, and player experience. Team effectiveness is maximized at a roughly moderate level of closure across the networks, suggesting that this is the optimal level of the group's network density. Guilds with high brokerage, meaning they have diverse connections with other groups, were more effective in achievement-oriented networks. In addition, guilds with central leaders were more effective when they teamed up with other guild leaders.
Grace A. Benefield, Cuihua Shen, Alex Leavitt
CSCW1