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
 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
 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
Other Working Papers
 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)
 Song, Jamie Seoyeon & Jason P. Davis. “What’s in a Name? Categorical and Idiosyncratic Identity of New Organizations in Nascent Markets”
 Song, Jamie Seoyeon. Going Beyond Conversational Partners: Entrepreneurs’ Framing and Audiences’ Support for Their Innovations
 Song, Jamie Seoyeon “Leveraging Ambiguity: Entrepreneurs’ Linguistic Ambiguity and Audiences' Support for Their Innovation"
Research in Progress
 Female entrepreneurs’ communication of their ventures (with Tatiana Lluent)
 Social relationships and development of ideas for innovation (with Gianluca Carnabuci and Linus Dahlander)
 Optimal distinctiveness and landscape dimensionality (with Tian Chan and Yonghoon Lee)
 Using Reddit and Twitter conversations to detect meaning formation (with Hallie Cho)