Abstract
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.
This work is base on an earlier work: Looking for Great Ideas - Analyzing the Innovation Jam in WebKDD/SNA-KDD ’07: Proceedings of the 9th WebKDD and 1st SNA-KDD 2007 workshop on Web mining and social network analysis ©ACM, 2007. http://doi.acm.org/10.1145/1348549.1348557
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Gryc, W. et al. (2009). Looking for Great Ideas: Analyzing the Innovation Jam. In: Zhang, H., et al. Advances in Web Mining and Web Usage Analysis. SNAKDD 2007. Lecture Notes in Computer Science(), vol 5439. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-00528-2_2
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DOI: https://doi.org/10.1007/978-3-642-00528-2_2
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