COINs change leaders - Lessons Learned from a Distributed Course

In this paper we analyze the communication network of 50 students from five universities in three countries participating in a joint course on Collaborative Innovation Networks (COINs). Students formed ten teams. Interaction variables calculated from the e-mail archive of individual team members predict the level of creativity of the team. Oscillating leadership, where members switch between central and peripheral roles is the best predictor of creativity, it is complemented by the variance in the amount of sending or receiving information, and by answering quickly, and positive language. We verify our automatically generated creativity metrics with interviews.

[1]  Peter A. Gloor,et al.  JazzFlow—Analyzing “Group Flow” Among Jazz Musicians Through “Honest Signals” , 2012, KI - Künstliche Intelligenz.

[2]  Yan Zhao,et al.  Visualization of Communication Patterns in Collaborative Innovation Networks - Analysis of Some W3C Working Groups , 2003, CIKM '03.

[3]  E. Salas,et al.  Facilitating Innovation in Diverse Science Teams Through Integrative Capacity , 2012 .

[4]  Leonard M. Freeman,et al.  A set of measures of centrality based upon betweenness , 1977 .

[5]  Detlef Schoder,et al.  Analysis of Informal Communication Networks – A Case Study , 2009, Bus. Inf. Syst. Eng..

[6]  B. Tuckman.  DEVELOPMENTAL SEQUENCE IN SMALL GROUPS. , 1965, Psychological bulletin.

[7]  Daniel Olguin Olguin,et al.  Sociometric badges : wearable technology for measuring human behavior , 2007 .

[8]  Alex Pentland,et al.  Capturing Individual and Group Behavior with Wearable Sensors , 2009, AAAI Spring Symposium: Human Behavior Modeling.

[9]  T. M. Amabile.  The social psychology of creativity , 1984 .

[10]  Peter A. Gloor,et al.  Social capital increases efficiency of collaboration among Wikipedia editors , 2011, HT '11.

[11]  Peter A. Gloor,et al.  Capturing team dynamics through temporal social surfaces , 2005, Ninth International Conference on Information Visualisation (IV'05).

[12]  Daniel Olguín Olguín,et al.  Towards “Honest Signals” of Creativity – Identifying Personality Characteristics Through Microscopic Social Network Analysis , 2011 .

[13]  D. Simonton.  After Einstein: Scientific genius is extinct , 2013, Nature.

[14]  A. Pentland,et al.  The Virtual Mirror - Reflecting on Social and Psychological Self to Increase Organizational Creativity , 2010 .

[15]  Jonathon N. Cummings,et al.  Structural properties of work groups and their consequences for performance , 2003, Soc. Networks.

[16]  Martin H. Levinson.  Creativity: Flow and the Psychology of Discovery and Invention , 1997 .

[17]  Detlef Schoder,et al.  Finding collaborative innovation networks through correlating performance with social network structure , 2008 .

[18]  Robert R. McCrae,et al.  The NEO–PI–3: A More Readable Revised NEO Personality Inventory , 2005, Journal of personality assessment.

[19]  K. Fischbach,et al.  Measuring social capital in creative teams through sociometric sensors , 2012 .

[20]  R. Spencer.  Group Genius: The Creative Power of Collaboration , 2008 .

[21]  Peter A. Gloor,et al.  Swarm Creativity: Competitive Advantage Through Collaborative Innovation Networks , 2006 .

[22]  Alex Pentland,et al.  Honest Signals - How They Shape Our World , 2008 .

[23]  C. Murray,et al.  Human Accomplishment: The Pursuit of Excellence in the Arts and Sciences, 800 B.C. to 1950 , 2003 .

[24]  Peter A. Gloor,et al.  Correlating temporal communication patterns of the Eclipse open source community with performance and creativity , 2007, Comput. Math. Organ. Theory.