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Research Interest

My research explores how organizational actors' social networks and communication contents flowing through the networks influence the evaluation of their audience. I am particularly interested in better understanding how entrepreneurs build social relationships and engage in communication with their audiences to gain support for their innovations. 

I use novel machine learning approaches to examine rich conversational data on online platforms such as Twitter, Amazon, Apple App Store, and Product Hunt

Refereed Publications

[1] Greve, Henrich R., & Jamie Seoyeon Song. 2017. “Amazon Warrior: How a Platform Can Restructure Industry Power and Ecology” in Advances in Strategic Management, vol. 37

[2] Bodner, Julia*, Jamie Seoyeon Song*, & Gabriel Szulanski. 2019. “Heuristics to Navigate Uncertainties: Interview with Professor Kathleen M. Eisenhardt” Journal of Management Inquiry, 28(3): 359-365

*equal authorship

Other Working Papers

[3] Song, Jamie Seoyeon & Martin Gargiulo. “Does Controversy Trigger Engagement?
The Contrasting Effects of Opinion Divergence on Exchanges in Online Networks" – Academy of Management Journal (2nd Round Revise and Resubmit)

[4] Song, Jamie Seoyeon & Jason P. Davis. “What’s in a Name? Categorical and Idiosyncratic Identity of New Organizations in Nascent Markets”

[5] Song, Jamie Seoyeon. Going Beyond Conversational Partners: Entrepreneurs’ Framing and Audiences’ Support for Their Innovations 

[6] Song, Jamie Seoyeon “Leveraging Ambiguity: Entrepreneurs’ Linguistic Ambiguity and Audiences' Support for Their Innovation" 

Research in Progress

[7] Female entrepreneurs’ communication of their ventures (with Tatiana Lluent) 


[8] Social relationships and development of ideas for innovation (with Gianluca Carnabuci and Linus Dahlander) 


[9] Optimal distinctiveness and landscape dimensionality (with Tian Chan and Yonghoon Lee) 


[10] Using Reddit and Twitter conversations to detect meaning formation (with Hallie Cho) 

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