Presentation made during the CSCW 2017 conference. Reference: Lykourentzou I., Kraut R. E., Dow S. P. (2017), Team Dating Leads to Better Online Ad Hoc Collaborations, 20th ACM Conference on Computer-Supported Cooperative Work and Social Computing, February 25 – March 1, Portland, USA.

1. Team Dating Leads to Better Online
Ad Hoc Collaborations
Ioanna Lykourentzou, Robert E. Kraut, Steven P. Dow

2. Ad-hoc virtual teams
Teams of individuals collaborating online, that have
not worked together in the past

3. Which factors make a team successful?
Individual
Skills
Past performance
Personality
Team-specific
Interpersonal compatibility
Work styles compatibility
Challenges for ad-hoc team formation
Skills not known or not a-priori definable
Team conflicts due to undetected poor dynamics

4. Can we quantify the skills and interpersonal
compatibility of a team, before its members
are officially assigned to work together?

5. Thin slicing
• Psychology principle: People can make accurate
inferences about others based on very brief
windows of experience.
• Applied to predict divorce rates in couples
[Buehlman, Gottman and Katz, 1992] and in
classroom setting [Curşeu et al., 2010]
• Usually applied on face-to-face settings

6. Team dating
People work with and rate each other in
multiple trial work sessions
Algorithm creates teams, maximizing skill
and interpersonal compatibility
Applied to crowdsourcing

7. Study design
Can crowd workers extract useful information
from team dating, to help make better teams?
Experiment 1
Can working with someone
briefly yield information that
cannot be extracted by an
external review of their work?
Experiment 2
Do teams formed using team
dating information lead to
better outcomes?
If so, why?

8. Experiment 1 - Task
“Enjoy every moment -
pleasure in the cup.”
“The coffee that
awakens your senses!”
“Make a slogan for a new coffee product”

9. Experiment 1: Setup
Team dating Teammate selection
Round 1 Round 2 Round 3
Individual task
External
evaluation
3:00 3:00 x 3
Individual skill
Other’s ratings

10. Experiment 1: What matters in teammate
selection?
• Individual skill
• Matters only when selecting from all possible
teammates (p<.05)
• Does not matter when restricted to dates
• Other people’s opinion
• Does not matter when selecting a teammate
• Dating experience
• Having worked with a person predicts selection when
considering all possible teammates (p<.001)
• Personal preference matters (p<.05)

11. Team dating affects teammate
selection, but can we use this
information to form effective teams?

12. Experiment 2: Extending Experiment 1
• Algorithm forms teams using:
• Personal preferences (dyad-specific ratings)
• Whether they have dated or not
• Three conditions
Preferred dates
Random dates
Random non-dates
Does building teams using
personal preferences improve
team performance?
Does having worked
together during team dating
improve team performance?

13. Experiment 2: Team Formation Algorithm
Not good collaboration Excellent collaboration
Alice Bob
Dan
Carol
Eve
Frank
Alice Bob
Dan
Carol
Eve
Frank Frank
1st round 2nd round
Alice Bob
Dan
Carol
Eve
3rd round
Alice Bob
Dan
Carol
Eve
Frank
Alice Bob
Dan
Carol
Eve
Frank
Preferred dates Random dates Random non dates
Alice Bob
Dan
Carol
Eve
Frank
Team formation
algorithm

14. Experiment 2 - Task
EndAIDS
“Help EndAIDS. For
a better world. For
our future.”
“Refreshment in
every drop, Your
new favorite coffee.”
“AIDS is not the end.
Never stop fighting,
never stop learning.
Join EndAIDS”
Team dating phase: “Make a slogan for a new coffee product”
Main task phase: “Make a slogan for a non-profit organization”

15. Experiment 2: Setup
3:00 3:00 x 3 8:00
Team dating
Round 1 Round 2 Round 3
Individual task Team formation (algorithm)
Preferred dates
Random dates
Random non-
dates
External evaluation External evaluation

16. Experiment 2: How does team dating affect
team performance?
Preferred dates outperform the other conditions
1.0
1.5
2.0
2.5
3.0
3.5
4.0
4.5
Preferred dates Random dates Random non-dates
Preferred vs. Random dates (p<.001), Preferred vs. Random non-dates (p<.05)
Team’s
slogan
quality

17. Experiment 2: How does team dating affect
team performance?
• Yes, partially due to personal preferences
• Not explained by individual skill or other people’s ratings
Preferred Dates
vs.
Random Dates
Team Slogan
Quality
Teammate’s
evaluation from
team date
Preferred dates
Random dates
Does building teams using
personal preferences improve
team performance?

18. • No. Simply having worked together does not improve
team performance (p=.18)
Random dates
Random non-dates
Does having worked
together during team dating
improve team performance?
Experiment 2: How does team dating affect
team performance?

19. Take-home findings
• Team dating yields information that:
• Cannot be extracted by an external review of individual
work
• Can be used to automatically create more effective
teams
• Team dating benefits:
• Due to dyad-specific interpersonal preferences
• Not due to individual skills, general teamwork ability, or
learning to work together

20. Future work
• How does the medium (e.g. video vs. text) affect team
dating?
• How can this technique be applied to different tasks and
settings?
• Teammate selection mechanisms?
• Social/cultural affinity signals
• Individual work similarity, common ground
• Trust, perceived aptness
• Turn-taking style similarity
• Communication equableness etc.

21. Thank you for your attention!
ioanna.lykourentzou@list.lu
robert.kraut@cmu.edu
spdow@ucsd.edu

22. 1. Justin S. Albrechtsen, Christian A. Meissner, and Kyle J. Susa. 2009.
Can intuition improve deception detection performance? Journal of
Experimental Social Psychology 45, 4: 1052–1055.
2. Nalini Ambady and John Joseph Skowronski. 2008. First impressions.
First Impressions 31, 1: 368.
3. Kim T. Buehlman, John M. Gottman, and Lynn F. Katz. 1992. How a
couple views their past predicts their future: Predicting divorce from an
oral history interview. Journal of Family Psychology 5, 3–4: 295–318.
4. Petru L Curşeu, Patrick Kenis, Jörg Raab, et al. 2010. Composing
Effective Teams through Team Dating. Organization Studies 31, 7:
873–894.
5. Michael W. Kraus and Dacher Keltner. 2009. Signs of socioeconomic
status: A thin-slicing approach. Psychological Science 20, 1: 99–106.
6. Paul E Stillman, Thomas Gilovich, and Kentaro Fujita. 2014.
Predicting group outcomes from brief exposures. Social Cognition 32,
1: 71–82.
References