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Article: Video mining: Measuring visual information using automatic methods

TitleVideo mining: Measuring visual information using automatic methods
Authors
KeywordsVisual variation
Visual information
Video content
Video mining
Issue Date2019
Citation
International Journal of Research in Marketing, 2019, v. 36, n. 2, p. 216-231 How to Cite?
AbstractMarketers are becoming increasingly reliant on videos to market their products and services. However, there is no standard set of measures of visual information that can be applied to large datasets. This paper proposes two standard measures that can be automatically obtained from videos: visual variation and video content. The paper tests the measures on crowdfunding videos from a leading online crowdfunding website, and shows that the proposed measures have explanatory power on the funding outcomes of the projects. These measures can be effectively implemented and used for large datasets. Further, researchers can apply these measures to other sets of visual information, and marketers could use the research to guide their video design and improve their video marketing effectiveness.
Persistent Identifierhttp://hdl.handle.net/10722/302225
ISSN
2023 Impact Factor: 5.9
2023 SCImago Journal Rankings: 3.352
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorLi, Xi-
dc.contributor.authorShi, Mengze-
dc.contributor.authorWang, Xin (Shane)-
dc.date.accessioned2021-08-30T13:58:03Z-
dc.date.available2021-08-30T13:58:03Z-
dc.date.issued2019-
dc.identifier.citationInternational Journal of Research in Marketing, 2019, v. 36, n. 2, p. 216-231-
dc.identifier.issn0167-8116-
dc.identifier.urihttp://hdl.handle.net/10722/302225-
dc.description.abstractMarketers are becoming increasingly reliant on videos to market their products and services. However, there is no standard set of measures of visual information that can be applied to large datasets. This paper proposes two standard measures that can be automatically obtained from videos: visual variation and video content. The paper tests the measures on crowdfunding videos from a leading online crowdfunding website, and shows that the proposed measures have explanatory power on the funding outcomes of the projects. These measures can be effectively implemented and used for large datasets. Further, researchers can apply these measures to other sets of visual information, and marketers could use the research to guide their video design and improve their video marketing effectiveness.-
dc.languageeng-
dc.relation.ispartofInternational Journal of Research in Marketing-
dc.subjectVisual variation-
dc.subjectVisual information-
dc.subjectVideo content-
dc.subjectVideo mining-
dc.titleVideo mining: Measuring visual information using automatic methods-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1016/j.ijresmar.2019.02.004-
dc.identifier.scopuseid_2-s2.0-85063268647-
dc.identifier.volume36-
dc.identifier.issue2-
dc.identifier.spage216-
dc.identifier.epage231-
dc.identifier.isiWOS:000474504000004-

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