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)