Looking for great ideas: analyzing the innovation jam

ABSTRACT

We discuss the Innovation Jam that IBM carried out in 2006, with the objective of identifying innovative and promising "Big Ideas" through a moderated on-line discussion between IBM worldwide employees and external contributors. We describe the data available and investigate several analytical approaches to address the challenge of understanding "how innovation happens" and to facilitate the success of future Jams. We demonstrate the social network structure of data and its time dependence, and discuss the results of both supervised and unsupervised learning applied to this data.

REFERENCES

• 1: Rakesh Agrawal , Sridhar Rajagopalan , Ramakrishnan Srikant , Yirong Xu, Mining newsgroups using networks arising from social behavior, Proceedings of the 12th international conference on World Wide Web, May 20-24, 2003, Budapest, Hungary [doi>10.1145/775152.775227]
• 2: R. Albert and A.-L. Barabasi. Statistical mechanics of complex networks. Reviews of Modern Physics, 74(1):47--97, January 2002.
• 3: V. Batagelj and A. Mrvar. Pajek - program for large network analysis. Connections, 2(21):47--57, 1998.
• 4: Chris Buckley , Gerard Salton , James Allan, The effect of adding relevance information in a relevance feedback environment, Proceedings of the 17th annual international ACM SIGIR conference on Research and development in information retrieval, p.292-300, July 03-06, 1994, Dublin, Ireland
• 5: W. J. Conover. Practical nonparametric statistics. New York: John Wiley and Sons, 1971.
• 6: Daniel Gruhl , R. Guha , David Liben-Nowell , Andrew Tomkins, Information diffusion through blogspace, Proceedings of the 13th international conference on World Wide Web, May 17-20, 2004, New York, NY, USA [doi>10.1145/988672.988739]
• 7: C. Halverson, J. Newswanger, T. Erickson, T. Wolf, W. A. Kellogg, M. Laff, and P. Malkin. World jam: Supporting talk among 50,000+. ECSCW'2001: European Conference on Computer-Supported Cooperative Work, Bonn, Germany, 2001.
• 8: J. Hempel. Big blue brainstorm. Business Week, August 2006.
• 9: A. K. Jain and R. C. Dubes. Algorithms for clustering data. Prentice-Hall, Inc., Upper Saddle River, NJ, USA, 1988.
• 10: Jon Kleinberg, The small-world phenomenon: an algorithm perspective, Proceedings of the thirty-second annual ACM symposium on Theory of computing, p.163-170, May 21-23, 2000, Portland, Oregon, United States [doi>10.1145/335305.335325]
• 11: P. Kolari, T. Finin, K. Lyons, Y. Yeshaa, Y. Yesha, S. Perelgut, and J. Hawkins. On the structure, properties and utility of internal corporate blogs. In International Conference on Weblogs and Social Media, 2007.
• 12: Catherine Lasser, Discovering Innovation, Proceedings of the IEEE International Conference on e-Business Engineering, p.4, October 24-26, 2006 [doi>10.1109/ICEBE.2006.42]
• 13: J. Travers and Milgram. An experimental study of the small world problem. Sociometry, 32(4):425--443, 1969.