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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“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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“…goûts ont été théorisés comme étant soumis à des mécanismes d’influence sociale se diffusant à travers des structures de réseaux sociaux complexes (Salganik et al., 2006) et, plus particulièrement, les goûts des producteurs ont été pensés comme dépendant de positionnements statutaires dans des…”
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“For example, [18], [16] and [14] showed that experimental manipulations arbitrarily signaling the seeming prior “success” of products on Kickstarter, downloadable songs, and articles on a social news aggregation website, respectively, led users to favorable online behavior toward these perceived…”
BackgroundOnline Content Trading: Sharing Mart System and Auction Experiments
İnaltekin, H., Ozgencil, N. E., Xu, H. F., et al. (2010) · IEEE International Conference on Communications workshops · doi:10.1109/iccw.2010.5503928 · Cited by 3
Just-in-Time Social Cloud: Computational Social Platform to Guide People's Just-in-Time Decisions
Lee, K. H., Lippman, A., Pentland, A., & Maes, P. (2013) · IEEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData) · doi:10.1109/greencom-ithings-cpscom.2013.219 · Cited by 3
Clément, M., Papies, D., & Albers, S. (2008) · Gabler eBooks · doi:10.1007/978-3-8349-9916-0_4 · Cited by 3
Equity-Based Crowdfunding: Allowing the Masses to Take a Slice of the Pie
Stemler, A. (2016) · Emerald Group Publishing Limited eBooks · doi:10.1108/978-1-78560-315-020151013 · Cited by 3
Systemic Concentration in Sponsored Search Markets
Gupta, A., Saha, B., & Sarkar, U. K. (2016) · ACM Transactions on Management Information Systems · doi:10.1145/2934695 · Cited by 3
“…costs [Bakos 1997] and ease of listing [Brynjolfsson et al. 2011], is the presence of reinforcement mechanism(s) whereby popular products are placed higher in the product search listing, giving these products even more popularity in the future [Fleder and Hosanager 2009; Salganik et al. 2006].”
BackgroundFromI Love Lucyin Connecticut toDesperate Housewives’Wisteria Lane: Suburban TV Shows, 1950-2007
Miller, B. J. (2017) · Sociological Focus · doi:10.1080/00380237.2017.1283180 · Cited by 3
“As a whole, culture industries (television, movies, music, print, etc.) have difficulty predicting which products will be successful, since a range of factors – such as the behavior of other consumers (Salganik, Dodds, and Watts 2006; Salganik and Watts 2009) – affect popularity.”
BackgroundLundy, D. E., Stephens, L. A., Hinners, C. T., & Whitton, J. R. (2017) · Psychology of Aesthetics Creativity and the Arts · doi:10.1037/aca0000111 · Cited by 3
Menezes, M. B. C., da Silveira, G. J. C., & Guimaraes, R. (2018) · International Journal of Production Economics · doi:10.1016/j.ijpe.2018.01.013 · Cited by 3
Ranking-based rich-get-richer processes
Analytis, P. P., Gelastopoulos, A., & Stojić, H. (2023) · The Annals of Applied Probability · doi:10.1214/22-aap1921 · Cited by 3
Wang, X. (2020) · Journal of Mathematical Sociology · doi:10.1080/0022250x.2020.1746297 · Cited by 3
The Arbitrariness of Aesthetic Judgment
Sackris, D. C. (2020) · The Journal of Value Inquiry · doi:10.1007/s10790-020-09759-w · Cited by 3
Hit Song Prediction based on Gradient Boosting Decision Tree
Pham, B.-D., Tran, M., & Pham, H.-L. (2020) · NAFOSTED Conference on Information and Computer Science (NICS) · doi:10.1109/nics51282.2020.9335886 · Cited by 3
“In addition to exploiting information inside songs, some works [6], [7] also perform analysis to exploit the metadata of the songs.”
Background
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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