Ordinal classification/regression for analyzing the influence of superstars on spectators in cinema marketing

This paper studies the influence of superstars on spectators in cinema marketing. Casting superstars is a common risk-mitigation strategy in the cinema industry. Anecdotal evidence suggests that the presence of superstars is not always a guarantee of success and hence, a deeper study is required to...

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Autores: Montañés Roces, Elena|||0000-0003-0609-8945, Suárez Vázquez, Ana|||0000-0003-4257-9367, Quevedo Pérez, José Ramón|||0000-0001-7211-4312
Tipo de recurso: artículo
Fecha de publicación:2014
País:España
Institución:Universidad de Oviedo (UNIOVI)
Repositorio:RUO. Repositorio Institucional de la Universidad de Oviedo
Idioma:inglés
OAI Identifier:oai:digibuo.uniovi.es:10651/32976
Acceso en línea:http://hdl.handle.net/10651/32976
https://dx.doi.org/10.1016/j.eswa.2014.07.011
Access Level:acceso abierto
Palabra clave:Ordinal classification
Ordinal regression
Machine learning
Cinema marketing
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spelling Ordinal classification/regression for analyzing the influence of superstars on spectators in cinema marketingMontañés Roces, Elena|||0000-0003-0609-8945Suárez Vázquez, Ana|||0000-0003-4257-9367Quevedo Pérez, José Ramón|||0000-0001-7211-4312Ordinal classificationOrdinal regressionMachine learningCinema marketingThis paper studies the influence of superstars on spectators in cinema marketing. Casting superstars is a common risk-mitigation strategy in the cinema industry. Anecdotal evidence suggests that the presence of superstars is not always a guarantee of success and hence, a deeper study is required to analyze the potential audience of a movie. In this sense, knowledge, attitudes and emotions of spectators towards stars are analyzed as potential factors of influencing the intention of seeing a movie with stars in its cast. This analysis is performed through machine learning techniques. In particular, the problem is stated as an ordinal classification/regression task rather than a traditional classification or regression task, since the intention of watching a movie is measured in a graded scale, hence, its values exhibit an order. Several methods are discussed for this purpose, but Support Vector Ordinal Regression shows its superiority over other ordinal classification/regression techniques. Moreover, exhaustive experiments carried out confirm that the formulation of the problem as an ordinal classification/regression is a success, since powerful traditional classifiers and regressors show worse performance. The study also confirms that talent and popularity expressed by means of knowledge, attitude and emotions satisfactorily explain superstar persuasion. Finally, the impact of these three components is also checkedThis research has been partially supported by the Spanish Ministerio de Econom a y Competitividad, grant TIN2011-23558Elsevier20142014-01-01journal articlehttp://purl.org/coar/resource_type/c_6501AMhttp://purl.org/coar/version/c_ab4af688f83e57aainfo:eu-repo/semantics/articlehttp://hdl.handle.net/10651/32976https://dx.doi.org/10.1016/j.eswa.2014.07.011reponame:RUO. Repositorio Institucional de la Universidad de Oviedoinstname:Universidad de Oviedo (UNIOVI)Inglésengopen accesshttp://purl.org/coar/access_right/c_abf2Attribution-NonCommercial-NoDerivatives 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessoai:digibuo.uniovi.es:10651/329762026-06-07T06:38:51Z
dc.title.none.fl_str_mv Ordinal classification/regression for analyzing the influence of superstars on spectators in cinema marketing
title Ordinal classification/regression for analyzing the influence of superstars on spectators in cinema marketing
spellingShingle Ordinal classification/regression for analyzing the influence of superstars on spectators in cinema marketing
Montañés Roces, Elena|||0000-0003-0609-8945
Ordinal classification
Ordinal regression
Machine learning
Cinema marketing
title_short Ordinal classification/regression for analyzing the influence of superstars on spectators in cinema marketing
title_full Ordinal classification/regression for analyzing the influence of superstars on spectators in cinema marketing
title_fullStr Ordinal classification/regression for analyzing the influence of superstars on spectators in cinema marketing
title_full_unstemmed Ordinal classification/regression for analyzing the influence of superstars on spectators in cinema marketing
title_sort Ordinal classification/regression for analyzing the influence of superstars on spectators in cinema marketing
dc.creator.none.fl_str_mv Montañés Roces, Elena|||0000-0003-0609-8945
Suárez Vázquez, Ana|||0000-0003-4257-9367
Quevedo Pérez, José Ramón|||0000-0001-7211-4312
author Montañés Roces, Elena|||0000-0003-0609-8945
author_facet Montañés Roces, Elena|||0000-0003-0609-8945
Suárez Vázquez, Ana|||0000-0003-4257-9367
Quevedo Pérez, José Ramón|||0000-0001-7211-4312
author_role author
author2 Suárez Vázquez, Ana|||0000-0003-4257-9367
Quevedo Pérez, José Ramón|||0000-0001-7211-4312
author2_role author
author
dc.subject.none.fl_str_mv Ordinal classification
Ordinal regression
Machine learning
Cinema marketing
topic Ordinal classification
Ordinal regression
Machine learning
Cinema marketing
description This paper studies the influence of superstars on spectators in cinema marketing. Casting superstars is a common risk-mitigation strategy in the cinema industry. Anecdotal evidence suggests that the presence of superstars is not always a guarantee of success and hence, a deeper study is required to analyze the potential audience of a movie. In this sense, knowledge, attitudes and emotions of spectators towards stars are analyzed as potential factors of influencing the intention of seeing a movie with stars in its cast. This analysis is performed through machine learning techniques. In particular, the problem is stated as an ordinal classification/regression task rather than a traditional classification or regression task, since the intention of watching a movie is measured in a graded scale, hence, its values exhibit an order. Several methods are discussed for this purpose, but Support Vector Ordinal Regression shows its superiority over other ordinal classification/regression techniques. Moreover, exhaustive experiments carried out confirm that the formulation of the problem as an ordinal classification/regression is a success, since powerful traditional classifiers and regressors show worse performance. The study also confirms that talent and popularity expressed by means of knowledge, attitude and emotions satisfactorily explain superstar persuasion. Finally, the impact of these three components is also checked
publishDate 2014
dc.date.none.fl_str_mv 2014
2014-01-01
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
AM
http://purl.org/coar/version/c_ab4af688f83e57aa
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv http://hdl.handle.net/10651/32976
https://dx.doi.org/10.1016/j.eswa.2014.07.011
url http://hdl.handle.net/10651/32976
https://dx.doi.org/10.1016/j.eswa.2014.07.011
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution-NonCommercial-NoDerivatives 4.0 International
http://creativecommons.org/licenses/by-nc-nd/4.0/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution-NonCommercial-NoDerivatives 4.0 International
http://creativecommons.org/licenses/by-nc-nd/4.0/
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:RUO. Repositorio Institucional de la Universidad de Oviedo
instname:Universidad de Oviedo (UNIOVI)
instname_str Universidad de Oviedo (UNIOVI)
reponame_str RUO. Repositorio Institucional de la Universidad de Oviedo
collection RUO. Repositorio Institucional de la Universidad de Oviedo
repository.name.fl_str_mv
repository.mail.fl_str_mv
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