Leading the Herd Astray: An Experimental Study of Self-Fulfilling Prophecies in an Artificial Cultural Market

By Matthew J. Salganik, Duncan J. Watts. 2008

276 citations recorded by the source corpus.

Individuals influence each others' decisions about cultural products such as songs, books, and movies; but to what extent can the perception of success become a “self-fulfilling prophecy”? We have explored this question experimentally by artificially inverting the true popularity of songs in an online “music market,” in which 12,207 participants listened to and downloaded songs by unknown bands. We found that most songs experienced self-ful- filling prophecies, in which perceived—but initially false—popularity became real over time. We also found, however, that the inversion was not self-fulfilling for the market as a whole, in part because the very best songs recovered their popularity in the long run. Moreover, the distortion of market information reduced the correlation between appeal and popularity, and led to fewer overall downloads. These results, although partial and speculative, suggest a new approach to the study of cultural markets, and indicate the potential of web-based experiments to explore the social psychological origin of other macrosocio- logical phenomena.

Subfields: Sociology and Political Science, Statistical and Nonlinear Physics

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Citations in the corpus

Leveraging Position Bias to Improve Peer Recommendation (2014, background): “We experimentally evaluate the effect of position bias, in contrast to previous studies of social influence [2,3,5,16].”
Quantifying Social Influence in an Online Cultural Market (2012, background): “Songs were shown in random order in the independent condition [1,6,7].”
Cultural Industries: Product–Market Characteristics, Management Challenges and Industry Dynamics (2015, unknown): “The highest level of support concerns the logic that sales result from information cascades through which consumers inform each other about products’ qualities (Beck 2007; De Vany and Lee 2001; De Vany and Walls 1996; Gaffeo et al. 2008; Gazley et al. 2011; Giles 2007; Godart and Mears 2009; Moul 20”
Disentangling the Effects of Social Signals (2014, background): “In this setting, which was experimentally investigated by the MusicLab study (Salganik et al., 2006; Salganik and Watts, 2008), social influence plays a largely informational role (Krumme et al., 2012).”
Web-based experiments for the study of collective social dynamics in cultural markets (2009, unknown): “In the experiments presented here, the download counts were updated honestly, but in another experiment we explored the possibility that manipulated download counts could create self-fulfilling prophecies (Salganik & Watts, 2008).”
The Benefits of Social Influence in Optimized Cultural Markets (2015, result): “In particular, Salganik et al suggested that social influence contributes to both unpredictability and inequality of success, with follow-up experiments confirming these initial findings [9–12] (see also [13] for a perspective on the MUSICLAB paper).”
Aligning Popularity and Quality in Online Cultural Markets (2021, background): “Unfortunately, popularity, which is easily distorted by noise in the process, is not a good proxy for quality: It leads to market unpredictability and even self-fulfilling prophecies, in which a perceived but initially false popularity becomes real over time (Salganik and Watts 2008).”
Taming the Unpredictability of Cultural Markets with Social Influence (2017, methodology): “In either case, the market share does not entirely reflect user preferences, which may lead to unsatisfied consumers and loss of demand [20].”
Algorithmic Cultures : Essays on Meaning, Performance and New Technologies (2016, background): “This means early winners can see that popularity compounded (Salganik and Watts 2008).”