Climb or jump - status-based seeding in user-generated content network

Lanz, Andreas U. ; Goldenberg, Jacob ; Shapira, Daniel ; Stahl, Florian

Document Type: Conference presentation
Year of publication: 2017
Conference title: 39th Annual Marketing Science Conference
Location of the conference venue: Los Angeles, CA
Date of the conference: 7-10th June 2017
Publication language: English
Institution: Business School > Quantitatives Marketing und Konsumentenverhalten (Stahl 2013-)
Subject: 330 Economics
Abstract: This paper addresses optimal seeding policies in user-generated content networks by challenging the role of influencers. Using data from SoundCloud, the world’s leading user-generated content network in the music domain, we study creators of music who seek to build and increase their follower base by 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 evidence 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 managerial implications for information dissemination and optimal seeding in user-generated content networks.

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