Superstars Power, Mining the Paths to Stars’ Persuasion

Ana Suarez-Vazquez () and Elena Montañés-Roces
Additional contact information
Ana Suarez-Vazquez: University of Oviedo
Elena Montañés-Roces: University of Oviedo

Computational Economics, 2017, vol. 49, issue 1, No 3, 67-81

Abstract: Abstract This paper analyzes the influence of star power on the cinema market. The study adopts two gauges of star power, one based on the industry’s opinion and one based on the market’s interest. The article merges contributions in the persuasion and cinema market literatures to examine the influence of star power over spectators. This study use machine learning methods based on support vector ordinal regression to analyze the paths to superstars’ persuasion. The present research shows differences in the persuasion effect of star power based on the industry and star power based on the market. Similarly, there are differences in the influence of star power among men and women. The results of this study help to explain the mixed findings of previous research on superstars’ power.

Keywords: Movie industry; Star power; Persuasion; Machine learning; Support vector ordinal regression (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s10614-015-9540-5 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:kap:compec:v:49:y:2017:i:1:d:10.1007_s10614-015-9540-5

Ordering information: This journal article can be ordered from
http://www.springer. ... ry/journal/10614/PS2

DOI: 10.1007/s10614-015-9540-5

Access Statistics for this article

Computational Economics is currently edited by Hans Amman

More articles in Computational Economics from Springer, Society for Computational Economics Contact information at EDIRC.
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().