We are happy to announce that Dr. Andreas Lanz from the University of Mannheim will give a guest talk on „Status-Based Seeding in User-Generated Content Networks“ in the PhD seminar on Quantitative Marketing Research.

Andreas Lanz is a postdoctoral researcher at the University of Mannheim. His research interests lie primarily in understanding and predicting individual as well as aggregate behavior in social systems, especially in two-sided markets such as user-generated content networks. In collaboration with Berlin-headquartered startup SoundCloud, the world’s largest user-generated content network in the domain of music, he has been challenging basic assumptions of influencer marketing by means of data-based simulations as well as empirical and analytical models.


Climb or Jump – Status-Based Seeding in User-Generated Content Networks

by Andreas Lanz (University of Mannheim), Jacob Goldenberg (IDC Herzliya and Columbia University), Daniel Shapira (Ben-Gurion University), and Florian Stahl (University of Mannheim)

This paper addresses optimal seeding policies in user-generated content networks by challenging the role of influencers. On such platforms, the content is generated and offered by individuals, small groups, and firms that are interested in self-promotion. Using data from SoundCloud, the world’s leading user-generated content network in the music domain, we study creators of music who seek to increase the exposure of their content by building and increasing their follower base through directing promotional actions to other users of the networking platform. Focusing on the network status of both creator and seeding targets, we find that, in particular, unknown creators of music do not benefit from seeding high-status users. In fact, it appears that unknown creators should ignore predominant seeding policies and slowly „climb“ across status levels of seeding targets rather than attempt to „jump“ towards those with the highest status. Our research extends the existing seeding literature by introducing the concept of risk to dissemination dynamics in online communications. We show that unknown creators of music do not seed specific status levels but rather choose a portfolio of seeding targets while solving risk versus return trade-offs. We discuss various managerial implications for information dissemination and optimal seeding in user-generated content networks.