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Analyzing superstars’ power using support vector machines

Author:
Suárez Vázquez, AnaUniovi authority; Quevedo Pérez, José RamónUniovi authority
Subject:

Cinema market

Star power

Persuasion

Machine learning

Publication date:
2015-12
Editorial:

Springer

Publisher version:
http://dx.doi.org/10.1007/s00181-015-0923-1
Citación:
Empirical Economics, 49(4), p. 1521-1542 (2015); doi:10.1007/s00181-015-0923-1
Descripción física:
p. 1521-1542
Abstract:

The main objective of this paper is to explain the influence that superstars have over spectators. The most significant contributions in the field of persuasion are discussed. This theoretical framework suggests some hypotheses that are tested using the data of an empirical study based on a survey of moviegoers. Support vector machine (SVM) is used for data analysis and pattern discovery. The SVM prediction capacity is benchmarked against that from a linear regression and multinomial logit. Results show that the SVM has considerable promise for analyzing spectators’ behavior. The results of this analysis allow us to extract some significant conclusions and implications for the process of creating and maintaining the power of a superstar

The main objective of this paper is to explain the influence that superstars have over spectators. The most significant contributions in the field of persuasion are discussed. This theoretical framework suggests some hypotheses that are tested using the data of an empirical study based on a survey of moviegoers. Support vector machine (SVM) is used for data analysis and pattern discovery. The SVM prediction capacity is benchmarked against that from a linear regression and multinomial logit. Results show that the SVM has considerable promise for analyzing spectators’ behavior. The results of this analysis allow us to extract some significant conclusions and implications for the process of creating and maintaining the power of a superstar

URI:
http://hdl.handle.net/10651/36709
ISSN:
0377-7332; 1435-8921
DOI:
10.1007/s00181-015-0923-1
Patrocinado por:

This research has been partially supported by the mobility programme of the Campus of International Excellence of the University of Oviedo

Id. Proyecto:

Universidad de Oviedo-CEI

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