The DOI matches its Crossref record; 20 of the 21 references it cites were found in a registry or an index.
Experimental Study of Inequality and Unpredictability in an Artificial Cultural Market
Abstract
Hit songs, books, and movies are many times more successful than average, suggesting that “the best” alternatives are qualitatively different from “the rest”; yet experts routinely fail to predict which products will succeed. We investigated this paradox experimentally, by creating an artificial “music market” in which 14,341 participants downloaded previously unknown songs either with or without knowledge of previous participants' choices. Increasing the strength of social influence increased both inequality and unpredictability of success. Success was also only partly determined by quality: The best songs rarely did poorly, and the worst rarely did well, but any other result was possible.
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In the citing paper
“Rosen's economics of superstars [21] shows formally that when the cost of serving additional consumers approaches zero, cultural markets concentrate rewards on a small number of winners regardless of marginal quality differences”
From AI as a Democratizing Force in Indie Game Development (2026) · cites this paper as [21]
In the citing paper
“The market-structure literature of §2.4 predicts what follows: superstar concentration under near-zero marginal cost [21], against which the long-tail alternative [22] is directly testable with the outcome data of Table 13, and choice-abundant markets whose winners are selected by social dynamics rather than quality gradients [23].”
From AI as a Democratizing Force in Indie Game Development (2026) · cites this paper as [21]
In the citing paper
“When considering inequality in heterogeneous populations, there are two distinct aspects to take into account-the dispersion of outcomes and the predictability of outcomes (Lynn, Podolny, & Tao, 2009;Salganik, Dodds, & Watts, 2006).”
From Relative Feedback Increases Disparities in Effort and Performance in Crowdsourcing Contests: Evidence from a Quasi-Experiment on Topcoder (2022) · cites this paper as Salganik, Dodds, & Watts, 2006
In the citing paper
“In the case of an inherent quality or virtue, more predictable outcomes imply more equality and fairness (Cook & Hegtvedt, 1983;Jasso, 1983;Salganik et al., 2006).”
From Relative Feedback Increases Disparities in Effort and Performance in Crowdsourcing Contests: Evidence from a Quasi-Experiment on Topcoder (2022) · cites this paper as Salganik et al., 2006
In the citing paper
“However, social success and quality of content are only partly correlated (Salganik et al., 2006).”
From Social Drivers and Algorithmic Mechanisms on Digital Media. (2024) · cites this paper as Salganik et al., 2006
In the citing paper
“in a classic experiment, the popularity of all but the very best and worst songs was shown to be more related to stochastic early positive reception by other users than by their inherent quality”
From Stewardship of global collective behavior (2021) · cites this paper as [87]
In the citing paper
“Moreover, the presence of a significant number of neutral individuals holding a random opinion and a low confidence level around these two attractive forces tends to increase the unpredictability of the final outcome [15].”
From Social Influence and the Collective Dynamics of Opinion Formation (2013) · cites this paper as [15]
In the citing paper
“In agreement with previous works [15], the collective outcome appears to be poorly predictable and strongly dependent on the initial conditions [36].”
From Social Influence and the Collective Dynamics of Opinion Formation (2013) · cites this paper as [15]
In the citing paper
“Although there is on average a positive relationship between quality and success [66]”
From Relative Citation Ratio (RCR): A New Metric That Uses Citation Rates to Measure Influence at the Article Level (2016) · cites this paper as [66]
In the citing paper
“the ultimate winners in such contests are determined not only by the intrinsic value of the work but also by more intangible social variables [66].”
From Relative Citation Ratio (RCR): A New Metric That Uses Citation Rates to Measure Influence at the Article Level (2016) · cites this paper as [66]
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“Rating and ranking systems, when applied to large idea corpuses, are prone to quickly locking, because of positive feedback loops, into fairly static and arbitrary idea rankings,: people do not have time to rate all ideas and thus tend to consider only ideas that have already received good ratings [23].”
The sound of salience: How platform design impacts consumption
Rackowitz, L., & Haampland, O. (2025) · Information Economics and Policy · doi:10.1016/j.infoecopol.2025.101144 · Cited by 4
Wide Social Influence and the Emergence of the Unexpected: An Empirical Test Using Spotify Data
Arvidsson, M., Hedström, P., & Keuschnigg, M. (2025) · Sociological Science · doi:10.15195/v12.a29 · Cited by 5
“In light of the conflicting evidence and divergent interpretations presented in the sociological literature on social-influence effects (Salganik et al. 2006; Salganik and Watts 2009; van de Rijt 2019), we have focused on “wide” social influence, a mechanism that can decouple collective outcomes…”
InfluentialSocial influence: The Usage History heuristic
Pradelski, B. (2023) · Mathematical Social Sciences · doi:10.1016/j.mathsocsci.2023.03.003 · Cited by 4
Atypicality and Accountability: Evidence from Five Experiments
Betancourt, N., Hoever, I. J., & Wezel, F. C. (2024) · Organization Science · doi:10.1287/orsc.2022.16937 · Cited by 4
Wang, C., Zhang, X., Gou, Z., & Wu, Y. (2024) · Humanities and Social Sciences Communications · doi:10.1057/s41599-024-03636-8 · Cited by 8
“Salganik et al. (2006) showed that in an environment where people can see the popularity ranking of songs, the initial popularity could greatly affect the fi nal download volume, compared with the quality of the song itself.”
Die analytische Soziologie: Soziale Mechanismen, DBO-Theorie und Agentenbasierte Modelle
Bornmann, L. (2010) · Österreichische Zeitschrift für Soziologie · doi:10.1007/s11614-010-0076-6 · Cited by 3
Mobile Sensing Technologies and Computational Methods for Collective Intelligence
Olguín, D. O., Madan, A., Cebrián, M., & Pentland, A. (2011) · Studies in computational intelligence · doi:10.1007/978-3-642-20344-2_21 · Cited by 4
Rankings as coordination games: the Dutch Top 2000 pop song ranking
Prinz, A. L. (2016) · Journal of Cultural Economics · doi:10.1007/s10824-016-9272-y · Cited by 4
Sun, H., Brashears, M. E., & Smith, E. B. (2021) · Cambridge University Press eBooks · doi:10.1017/9781108878296.040 · Cited by 4
Dugoin-Clément, C. (2022) · Question(s) de management · doi:10.3917/qdm.217.0024 · Cited by 5
Woody, R. H. (2021) · doi:10.1093/oso/9780197546598.001.0001 · Cited by 9
Vargas-Bianchi, L., Mateus, J.-C., Pecho-Ninapaytan, A., & Zambrano-Zuta, S. (2023) · First Monday · doi:10.5210/fm.v28i3.12678 · Cited by 6
Kim, Y., Kim, Y., Kim, D. H., et al. (2023) · Applied Sciences · doi:10.3390/app131911109 · Cited by 4
Trapido, D., & Koppman, S. (2023) · Research in Organizational Behavior · doi:10.1016/j.riob.2023.100193 · Cited by 4
Network reciprocity and inequality: The role of additional mixing links among social groups
Zhang, W. (2024) · Chaos Solitons & Fractals · doi:10.1016/j.chaos.2024.114857 · Cited by 4
Quantifying the impact of homophily and influencer networks on song popularity prediction
Reisz, N., Servedio, V. D. P., & Thurner, S. (2024) · Scientific Reports · doi:10.1038/s41598-024-58969-w · Cited by 4
“It has been observed that people tend to reproduce perceived song popularity that is presented to them, even if these have been heavily modified 38–40 .”
BackgroundLenart-Gansiniec, R., Czakon, W., & Meyer, N. (2025) · Review of Managerial Science · doi:10.1007/s11846-024-00797-3 · Cited by 4
“…the perspective of science, technology, engineering, and mathematics (STEM) (Par - rick and Chapman 2020), medicine (Bassi et al. 2020), psychology (Buhrmester et al. 2011), sociology (Salganik et al. 2006), political science (Berinsky et al. 2012 ) and information science (Lukyanenko et al. 2020).”
Evolution of cooperation with early social influence for explaining collective action
He, X., Li, G., & Du, H. (2024) · Chaos An Interdisciplinary Journal of Nonlinear Science · doi:10.1063/5.0242606 · Cited by 4
Beyond Words: An Experimental Study of Signaling in Crowdfunding
Dambanemuya, H. K., Choi, E., Gergle, D., & Horvát, E.-Á. (2025) · ACM Transactions on Computer-Human Interaction · doi:10.1145/3716381 · Cited by 5
“Prior work indicates that signaling is more likely to occur when it is difficult to establish the merit of a project based on its description [20, 80, 86, 108].”
Breaking Feedback Loops in Recommender Systems with Causal Inference
Krauth, K., Wang, Z., & Jordan, M. I. (2025) · ACM Transactions on Recommender Systems · doi:10.1145/3728372 · Cited by 15
Metadata
- Authors
- Salganik, M. J., Dodds, P. S., & Watts, D. J.
- Affiliations
- Santa Fe Institute (US)
- Corresponding author
- Salganik, Matthew J.
- Dodds, Peter Sheridan
- Watts, Duncan J.
- Venue
- Science
- Published
- 2006-02-10
- Volume
- 311
- Issue
- 5762
- Pages
- 854-856
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- OpenAlex
- W2147453867
- Cited by
- 2,231
- References
- 21
- Citations by year
- 2026: 168 · 2025: 104 · 2024: 102 · 2023: 123 · 2022: 103 · 2021: 231 · 2020: 104 · 2019: 130 · 2018: 131 · 2017: 142 · 2016: 121 · 2015: 123 · 2014: 133 · 2013: 92 · 2012: 122
- FWCI
- 116.70
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Science (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Experimental Behavioral Economics Studies
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Complex Systems and Time Series Analysis
- Social Sciences › Decision Sciences › General Decision Sciences › Decision-Making and Behavioral Economics
- Keywords
- cultural market, social influence, music download, product success, consumer choice
- MeSH terms
- Consumer Behavior, Culture, Forecasting, Humans, Interpersonal Relations, Music, Research Design, Social Behavior, Sociology, Internet
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