Algorithms for clustering data
Algorithms for clustering data
The effect of adding relevance information in a relevance feedback environment
SIGIR '94 Proceedings of the 17th annual international ACM SIGIR conference on Research and development in information retrieval
The small-world phenomenon: an algorithmic perspective
STOC '00 Proceedings of the thirty-second annual ACM symposium on Theory of computing
Mining newsgroups using networks arising from social behavior
WWW '03 Proceedings of the 12th international conference on World Wide Web
Information diffusion through blogspace
Proceedings of the 13th international conference on World Wide Web
ICEBE '06 Proceedings of the IEEE International Conference on e-Business Engineering
Proceedings of the 6th International Conference on Ubiquitous Information Management and Communication
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In 2006, IBM hosted the Innovation Jam with the objective of identifying innovative and promising "Big Ideas" through a moderated on-line discussion among 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". Specifically, we examine whether it is possible to identify characteristics of such discussions that are more likely to lead to innovative ideas as identified by the Jam organizers. 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.