The economics of social media (super-)stars: an empirical investigation of stardom and success on YouTube

ABSTRACT

A new type of superstars developed with the rise of social media markets: social media superstars (SMS). The economic literature on the superstar phenomenon provides empirical evidence on different types of stars, above all athletes and musicians. This paper presents the first empirical work on SMS with original data from YouTube. Using various econometric techniques, we analyze a unique sample of 200 YouTube stars out of four different video categories to shed light on this new phenomenon. Beyond applying classic economic concepts on superstars by Rosen, MacDonald, and Adler, we contribute to extending the literature toward attention economics and the concepts of audience building (audience attraction and maintenance). In our empirical analysis, we find evidence supporting an inverse U-shape influence of upload frequency on the success of SMS. Moreover, we find empirical evidence that the duration and experience in the market have a significant influence on social media success. Eventually, we derive implications for superstar theory, SMS management, service providers, and advertisers.

Acknowledgments

The paper was presented at the World Media Economics & Management Conference (WMEMC) and the Royal Economic Society Annual Conference (RES). We thank the participants of the RES and WMEMC, the participants of the TU Ilmenau Research Platform meeting, as well as the participants of the 49th Hohenheimer Oberseminar, especially Sonja Rinne, and Thomas Grebel, for valuable comments on earlier versions of the paper. Furthermore, we thank the Office for Gender Equity (TU Ilmenau) for supporting the WMEMC conference attendance of Sophia Gaenssle. We are also grateful for the very valuable comments of the anonymous review team, the language assistance of Barbara Ann Güldenring, and the editorial assistance of Milan Lange and Mona Bader.

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

¹ See Hudders et al. (2020) for detailed literature review on strategic use of social media stars and influencer marketing.

² Being a top gamer or make-up artist requires, for instance, different skills than posting lifestyle vlogs (video blogs).

³ A lot of economic literature focuses on attention economics in advertising markets and competition models (see for example: Anderson & Coate, 2005; Anderson et al., 2018; Athey et al., 2018).

⁴ Newer data is not available and the data set not expandable due to limited historical data on the platform statfire.

⁵ statfire changed its’ strategy in 2017, only specific accounts can be searched at the moment (July 2020).

⁶ The categories are defined and offered by YouTube itself. The content provider can choose in which category her videos belong. The sample was checked and all accounts within the sample are straightforward suitable for the named category.

⁷ See Appendix for full correlation table.

⁸ Calculating back the log-log model (example for Model 2):$\frac{d}{dx}(-79.160x^2+991.232x-3,084.591)=991.232-158.32x$ $x\approx 6.261$, therefore: $e^{6.261}\approx 523.742$ Due to shift along the x-axis for log-model (deleted videos, which meant negative uploads), we need to subtract the previously added number: $523.742-457=66.742$.

Additional information

Notes on contributors

Oliver Budzinski

Oliver Budzinski (Ph. D.) is Professor of Economic Theory and Director of the Institute of Economics at Ilmenau University of Technology, Germany. His research interests include Media Economics, Competition Policy and Industrial Economics, Cultural Economics as well as Sports Economics.

Sophia Gaenssle

Sophia Gaenssle (M. Sc.) is junior researcher at the chair of Economic Theory at the Ilmenau University ofTechnology, Germany. She specializes in media and cultural economics, with particular emphasison industrial organisation and digital markets.