Noshir Contractor – understanding and enabling collaboration [cictf11]

Dr. Contractor is professor of Behavioral Sciences at Northwestern.

Starting with dogs! SNIF – social networking in fur. Device goes on dog’s collar. Digs exchange business card info when close. “social petworking”

Lovegety – little device programmed with food music and movies you like. Flashes in proximity of potential love interest. When asking undergrads who likes this technology, it’s the engineering students, regardless of gender.

These are examples of use of technology to find the right people to connect with. Types of tech we have now are made by engineers for engineers. Important for people in IT space to work closely with social science knowledge.

First use of tech is to substitute. Not enough to offset or justify investments. 2nd stage is enlargement – technology increases activity. Technology increases gap between haves and have-nots. Part of what we need to do is to think creatively about how to reduce that gap. Productivity paradox – investment in IT doesn’t necessarily show return. Why? Giving Pony Express riders cell phones to call ahead to ask for water. Need to achieve 3rd stage – reconfiguration.

Ascendance of teams –
More research being done in teams
Research in teams has a higher impact.
Those in different disciplines have higher impact yet
And those involving different disciplines across different campuses have the highest impact.

But another study found that interdisciplinary distributed research is less likely to succeed. So how do we build tools to enable successful collaboration?

Understanding team assembly is key, and this is a very good time to do that.

Why do we form teams? In past, teams were assigned. But increasingly teams are self-forming. Sometimes based on self-interest. Or it may be based on social exchange. Or mutual interest and collective action. Contagion (everybody wants to work with the popular person). Balance – friends of friends. Homophily (birds of a feather). Proximity – form links with people close by – if you look at your buddy lists, most are people close by. Using tech to facilitate proximate communication. Each of these motivations have a structural signature. If you know what drives these networks, you can understand how to make them better.

Multidimensional network – not all nodes are people. Also includes documents, datasets, etc. Linked Open Data – publicly connecting datasets.

Team assembly for interdisciplinary NSF. When assembling a team, want high productivity from diversity, but also want smooth coordination stemming from shared cognitive models. How do we assemble teams to do both? 1,103 grant proposals submitted to NSF in 2 interdisciplinary programs. Researchers not likely to randomly form collaboration with each other. Researchers from top tier institutions are less likely to collaborate. Those with higher tenure are most likelybto collaborate. Researchers with high H-index are less likely to collaborate. Researchers are more likelynto collaborate with those they’ve collaborated with before.

Women are more likely to collaborate on funded proposals.
Odds of funding are higher when you collaborate with someone you’ve previously co-authors with, but not cited.

Exemplar 2 – massively multiplayer games. Virtual world exploratorium. Need to work with different characters to be successful. Motivations for creating teams in this context – selectivity and transivity (friend of friend) exists. Homophily of age and experience is supported. Short distances are important. Gender matters.

Are more diverse groups more successful? Uses Blau’s index to measure. Is group cosmopolitan characteristics more successful? Found diversity helps groups achieve more. Being more cosmopolitan helps avoid losses.

Using this data to build “match-making” Systems for forming research teams.

Initial relationships across disciplines are being encouraged by funding agencies and institutions. Need to keep those relationships fresh and not homogenize interests.

In multi-team systems the connections between the teams is more important than the connections within each team. ABC dimensions – Affective, Behavioral, Cognitive.

Different kinds of goals for teams – exploring, exploiting, mobilizing, bonding, swarming.


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