Creativity in Dynamic Social Networks

Motivation

”Outstanding discoveries, insights, and developments do not happen in a vacuum.”—Nobel Laureate Tom Steitz, on the impacts of peer interactions on research

Socio-cognitive soft skills such as creativity will play an ever-larger role in the tasks humans accomplish in the future of work. Although typically perceived as individual strength, creativity has a strong social component as people may find inspiration from others in their social networks (e.g., in networks among researchers, designers, or marketers). Real social networks self-organize with time, as people make and break social ties all the time. What impact does such self-organization have on people’s idea-generation performances?

In this project, we study idea generation performances of people in self-organizing social networks. Through a series of randomized experiments, we document how a social network’s connections and creative outcomes co-evolve in response to its members’ creative performance, popularity, and identity attributes. We capture insights in suitable models and design interventions to elevate creative performances.

Key Findings

People’s imagination can be triggered in many ways, one of those being social stimulation where people are inspired by their social partners’ ideas. We find that highly creative individuals gain increasingly high visibility and centrality with time as peers in the network choose to seek inspiration from their ideas (N = 288) [1]. These top performers inspire novel ideas in their follower peers, but ironically, their disproportionate visibility also gives rise to redundancy in those peers’ ideas. We develop (1) an agent-based model to explore corner cases, and (2) a game-theoretic model to explain rational link-formation choices under various stimulation-redundancy trade-off scenarios.

In the presence of demographic identity cues (gender/race), we find that (1) temporal link persistence becomes significantly influenced by homophily, and (2) inter-peer redundancies increase significantly compared to a demography-agnostic baseline, thereby hurting atypical thinking (N = 192) [2]. We use a statistical network model to mine link formation and link persistence patterns. These results inform a user interface intervention where concealing demographic cues can help elevate creative outcomes.

We observe that the presence of popularity signals (e.g., displaying follower counts on the screen) significantly influences inspiration-seeking links, partly by biasing people’s perception of their peers’ creativity. Using popularity signals as an external control in a randomized setting, we show causally that partially dispersing the centrality of top-performing individuals helps strike a balance between idea stimulation and redundancy to elevate creativity (N = 312) [3]. However, extreme dispersal leads to inferior creativity by narrowing the range of idea stimulation. This result informs top-down interventions (e.g., through policy decisions) that can improve the creative outcomes of a network.

We envision our work to inform managerial and algorithmic decision-making and public policy as it relates to helping humans become more creatively productive.