title: The benefits of social influence in optimized cultural markets.
abstract: Social influence has been shown to create significant unpredictability in cultural markets, providing one potential explanation why experts routinely fail at predicting commercial success of cultural products. As a result, social influence is often presented in a negative light. Here, we show the benefits of social influence for cultural markets. We present a policy that uses product quality, appeal, position bias and social influence to maximize expected profits in the market. Our computational experiments show that our profit-maximizing policy leverages social influence to produce significant performance benefits for the market, while our theoretical analysis proves that our policy outperforms in expectation any policy not displaying social signals. Our results contrast with earlier work which focused on showing the unpredictability and inequalities created by social influence. Not only do we show for the first time that, under our policy, dynamically showing consumers positive social signals increases the expected profit of the seller in cultural markets. We also show that, in reasonable settings, our profit-maximizing policy does not introduce significant unpredictability and identifies "blockbusters". Overall, these results shed new light on the nature of social influence and how it can be leveraged for the benefits of the market.
authors.affiliation: Optimization Research Group, National ICT Australia, Melbourne, Victoria, Australia; Melbourne School of Engineering, The University of Melbourne, Melbourne, Victoria, Australia.
authors.forename: Andrés
authors.initials: A
authors.lastname: Abeliuk
authors.affiliation: Optimization Research Group, National ICT Australia, Melbourne, Victoria, Australia; Centre for Business Analytics, Melbourne Business School, The University of Melbourne, Melbourne, Victoria, Australia.
authors.forename: Gerardo
authors.initials: G
authors.lastname: Berbeglia
authors.affiliation: Optimization Research Group, National ICT Australia, Melbourne, Victoria, Australia; Melbourne School of Engineering, The University of Melbourne, Melbourne, Victoria, Australia.
authors.forename: Manuel
authors.initials: M
authors.lastname: Cebrian
authors.affiliation: Optimization Research Group, National ICT Australia, Melbourne, Victoria, Australia; Research School of Computer Science, The Australian National University, Canberra, ACT, Australia.
authors.forename: Pascal
authors.initials: P
authors.lastname: Van Hentenryck
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D003469:Culture; D006801:Humans; D009146:Music; D000067074:Peer Influence; D012919:Social Behavior; D040241:Social Marketing
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