Visualizing Collective Idea Generation and Innovation Processes in Social Networks
Yiding Cao, Yingjun Dong, Minjun Kim, Neil G. MacLaren, Sriniwas, Pandey, Shelley D. Dionne, Francis J. Yammarino, and Hiroki Sayama

TL;DR
This paper introduces three innovative visualization methods to analyze and understand the complex, dynamic processes of collective idea generation and innovation within social networks, enhancing monitoring and analysis capabilities.
Contribution
The study develops and applies three novel visualization techniques—Idea Cloud, Idea Geography, and Idea Network—for better analysis of collective innovation in social networks.
Findings
Idea Cloud tracks idea clustering and transitions.
Idea Geography reveals the structure of idea space and collaboration.
Idea Network links idea dynamics with social influence patterns.
Abstract
Collective idea generation and innovation processes are complex and dynamic, involving a large amount of qualitative narrative information that is difficult to monitor, analyze, and visualize using traditional methods. In this study, we developed three new visualization methods for collective idea generation and innovation processes and applied them to data from online social network experiments. The first visualization is the Idea Cloud, which helps monitor collective idea posting activity and intuitively tracks idea clustering and transition. The second visualization is the Idea Geography, which helps understand how the idea space and its utility landscape are structured and how collaboration was performed in that space. The third visualization is the Idea Network, which connects idea dynamics with the social structure of the people who generated them, displaying how social influence…
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