Measuring and Optimizing Cultural Markets. Abeliuk, A., Berbeglia, G., Cebrian, M., & Van Hentenryck, P. arXiv, 2014. ![Measuring and Optimizing Cultural Markets [link]](https://bibbase.org/img/filetypes/link.svg "link")
Website abstract bibtex In their seminal paper (Science 311(5762), 2006), Salganik, Dodds, and Watts introduced an artificial music market (the MusicLab) to study why experts routinely fail at predicting commercial success of cultural products. The MusicLab was instrumental in demonstrating that social influence can create significant unpredictability in cultural markets. Watts ("Everything is obvious once you know the answer", Random House, 2012) also advocates the use of "measure and react" strategies to counteract the difficulty of making accurate predictions. However, finding a concrete strategy that scales for very large markets has remained elusive so far. This paper demonstrates the benefits of such a strategy in the MusicLab setting: It presents a "measure and react" strategy, called "measure and optimize", that combines songs quality, appeal, and social influence to maximize the expected downloads at each iteration. Computational experiments show that our "measure and optimize" strategy can leverage social influence to produce significant performance benefits for the market. Moreover, this paper formally proves that a "measure and optimize" strategy with social influence outperforms in expectation any "measure and react" strategy not displaying social information. In other words, when using a "measure and optimize" strategy, dynamically showing consumers positive social information increases the expected performance of the seller in the cultural market.
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title = {Measuring and Optimizing Cultural Markets},
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abstract = {In their seminal paper (Science 311(5762), 2006), Salganik, Dodds, and Watts introduced an artificial music market (the MusicLab) to study why experts routinely fail at predicting commercial success of cultural products. The MusicLab was instrumental in demonstrating that social influence can create significant unpredictability in cultural markets. Watts ("Everything is obvious once you know the answer", Random House, 2012) also advocates the use of "measure and react" strategies to counteract the difficulty of making accurate predictions. However, finding a concrete strategy that scales for very large markets has remained elusive so far. This paper demonstrates the benefits of such a strategy in the MusicLab setting: It presents a "measure and react" strategy, called "measure and optimize", that combines songs quality, appeal, and social influence to maximize the expected downloads at each iteration. Computational experiments show that our "measure and optimize" strategy can leverage social influence to produce significant performance benefits for the market. Moreover, this paper formally proves that a "measure and optimize" strategy with social influence outperforms in expectation any "measure and react" strategy not displaying social information. In other words, when using a "measure and optimize" strategy, dynamically showing consumers positive social information increases the expected performance of the seller in the cultural market.},
bibtype = {article},
author = {Abeliuk, Andrés and Berbeglia, Gerardo and Cebrian, Manuel and Van Hentenryck, Pascal},
journal = {arXiv}
}
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