The benefits of social influence in optimized cultural markets

PLoS ONE

Volumn 10, Issue 4, 2015, Pages

  Abeliuk, Andrés ^a,b   Berbeglia, Gerardo ^a,c   Cebrian, Manuel ^a,b   Van Hentenryck, Pascal ^a,d  

^a CSIRO   (Australia)

^b The University of Melbourne   (Australia)

^c The University of Melbourne   (Australia)

^d AUSTRALIAN NATIONAL UNIVERSITY   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHM; ARTICLE; COMMERCIAL PHENOMENA; CULTURAL MARKET; INTERNET; MARKET; POLICY; SOCIAL ASPECT; SOCIAL INFLUENCE; COMPUTER SIMULATION; CULTURAL ANTHROPOLOGY; HUMAN; MUSIC; PEER PRESSURE; SOCIAL BEHAVIOR; SOCIAL MARKETING;

ALGORITHMS; COMPUTER SIMULATION; CULTURE; HUMANS; MUSIC; PEER INFLUENCE; SOCIAL BEHAVIOR; SOCIAL MARKETING;

EID: 84926677312     PISSN: None     EISSN: 19326203     Source Type: Journal    
DOI: 10.1371/journal.pone.0121934     Document Type: Article

References (24)

1. Bielby WT, Bielby DD. All hits are flukes: Institutionalized decision making and the rhetoric of network prime-time program development. American Journal of Sociology. 1994;99(5):1287-1313.
2. Caves RE. Creative industries: Contracts between art and commerce. 20. Harvard University Press; 2000.
3. De Vany A. Hollywood Economics: How Extreme Uncertainty Shames the Film Industry. Routledge; 2011.
4. Hirsch PM. Processing fads and fashions: An organization-set analysis of cultural industry systems. American journal of sociology. 1972:639-659.
5. Peterson RA, Berger DG. Entrepreneurship in Organizations: Evidence from the Popular Music Industry. Administrative Science Quarterly. 1971;16 (1). doi: 10.2307/2391293
6. Watts DJ. Everything Is Obvious: How Common Sense Fails Us. Random House LLC; 2012.
7. Eliashberg J, Shugan SM. Film critics: Influencers or predictors? Journal of Marketing. 1997;61 (2). doi: 10.2307/1251831
8. Salganik MJ, Dodds PS, Watts DJ. Experimental study of inequality and unpredictability in an artificial cultural market. Science. 2006;311(5762):854-856.
9. Salganik MJ, Watts DJ. Web-Based Experiments for the Study of Collective Social Dynamics in Cultural Markets. Topics in Cognitive Science. 2009;1(3):439-468. doi: 10.1111/j.1756-8765.2009.01030.x PMID: 25164996
10. Salganik MJ, Watts DJ. Leading the herd astray: An experimental study of self-fulfilling prophecies in an artificial cultural market. Social Psychology Quarterly. 2008;71(4):338-355. doi: 10.1177/019027250807100404
11. Muchnik L, Aral S, Taylor SJ. Social influence bias: A randomized experiment. Science. 2013;341(6146):647-651. doi: 10.1126/science.1240466 PMID: 23929980
12. Van De Rijt A, Kang SM, Restivo M, Patil A. Field experiments of success-breeds-success dynamics. Proceedings of the National Academy of Sciences. 2014;111(19):6934-6939. doi: 10.1073/pnas. 1316836111
13. Hedström P. Experimental macro sociology: Predicting the next best seller. Science. 2006;311(5762):786-787. doi: 10.1126/science.1124707 PMID: 16469907
14. Krumme C, Cebrian M, Pickard G, Pentland S. Quantifying social influence in an online cultural market. PloS one. 2012;7(5):e33785. doi: 10.1371/journal.pone.0033785 PMID: 22590493
15. Shiller RJ. Market volatility. MIT press; 1992.
16. Shleifer A. Inefficient markets: An introduction to behavioral finance. Oxford university press; 2000.
17. Jensen MC. Some anomalous evidence regarding market efficiency. Journal of financial economics. 1978;6(2):95-101. doi: 10.1016/0304-405X (78) 90025-9
18. Lerman K, Hogg T. Leveraging Position Bias to Improve Peer Recommendation. PLOS ONE. 2014;9(6):1-8. doi: 10.1371/journal.pone.0098914
19. Shigeno M, Saruwatari Y, Matsui T. An algorithm for fractional assignment problems. Discrete Applied Mathematics. 1995;56(2):333-343. doi: 10.1016/0166-218X (93) 00094-G
20. Kabadi SN, Punnen AP. A strongly polynomial simplex method for the linear fractional assignment problem. Operations Research Letters. 2008;36(4):402-407. doi: 10.1016/j.orl.2007.12.001
21. Rigney D. The Matthew Effect. Columbia University Press; 2010.
22. Lorenz J, Rauhut H, Schweitzer F, Helbing D. How social influence can undermine the wisdom of crowd effect. Proceedings of the National Academy of Sciences. 2011;108(22):9020-9025. doi: 10. 1073/pnas.1008636108
23. Farrell S. Social influence benefits the wisdom of individuals in the crowd. Proceedings of the National Academy of Sciences. 2011;108(36):E625-E625. doi: 10.1073/pnas.1109947108
24. Rauhut H, Lorenz J, Schweitzer F, Helbing D. Reply to Farrell: Improved individual estimation success can imply collective tunnel vision. Proceedings of the National Academy of Sciences. 2011;108(36):E626-E626. doi: 10.1073/pnas.1111007108