Experimental Study of Inequality and Unpredictability in an Artificial Cultural Market

By Matthew J. Salganik, Peter Sheridan Dodds, Duncan J. Watts. 2006

2,129 citations recorded by the source corpus.

Subfields: Safety Research, Sociology and Political Science, Statistical and Nonlinear Physics

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Citations in the corpus

How algorithmic popularity bias hinders or promotes quality (2017, background): “created a music-sharing platform to determine under which conditions one can predict popular musical tracks [29].”
Why Amazon's Ratings Might Mislead You: The Story of Herding Effects (2014, neutral): “7,8 Through carefully designed control experiments in different settings, these studies demonstrate that disclosing prior collective opinions distorts individuals’ decision making as well as their perceptions of quality and value, creating herding that is irrational and pervasive, yet consequential…”
Leveraging Position Bias to Improve Peer Recommendation (2014, methodology): “Item ‘‘quality’’ varies significantly, although it is difficult to define or measure [2].”
The Paradox of Publicity (2014, background): “First, individuals may infer quality on the basis of popularity (e.g., Banerjee, 1992; Strang and Macy, 2001; Salganik, Dodds, and Watts, 2006).”
Blockbuster Culture's Next Rise or Fall: The Impact of Recommender Systems on Sales Diversity (2009, positive): “lar results were confirmed experimentally by Salganik et al. (2006).”
Web-based experiments for the study of collective social dynamics in cultural markets (2009, positive): “Details about song and band selection are available in the study of Salganik et al. (2006).”
Information Contagion: An Empirical Study of the Spread of News on Digg and Twitter Social Networks (2010, positive): “These distributions have been observed in a variety of contexts, including voting on Digg (Wu and Huberman 2007) and Essembly (Hogg and Szabo 2009), edits of Wikipedia articles (Wilkinson 2008), and music down-loads (Salganik, Dodds, and Watts 2006).”
The Dynamics of Audience Fragmentation: Public Attention in an Age of Digital Media (2012, background): “Most social media seem to offer some sort of measures that alert users to what their fellow consumers have done or said, often guiding subsequent choices (Cho & Roy, 2004; Salganik, Dodds, & Watts, 2006).”
Aligning Popularity and Quality in Online Cultural Markets (2021, methodology): “The quality ranking contrasts with the popularity ranking which was used in (Salganik, Dodds, and Watts 2006) to show the unpredictability caused by social influence in cultural markets.”
Nudge Effect of Fact-Check Alerts: Source Influence and Media Skepticism on Sharing of News Misinformation in Social Media (2020, background): “In other studies, website interface cueing via prevalence estimates has similarly been found to predict music downloads (Salganik et al., 2006) and online ticket purchases regardless of review valences (i.e., positive vs negative) (Liu, 2006).”
The Limits of Popularity-Based Recommendations, and the Role of Social Ties (2016, background): “Will unknown books become hits and vice-versa? How and how much will the habit of the typical reader change? A large body of work has investigated questions of this kind at the individual, user level [8, 25, 26, 35].”