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- Publisher Website: 10.1016/j.ijresmar.2019.02.004
- Scopus: eid_2-s2.0-85063268647
- WOS: WOS:000474504000004
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Article: Video mining: Measuring visual information using automatic methods
Title | Video mining: Measuring visual information using automatic methods |
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Authors | |
Keywords | Visual variation Visual information Video content Video mining |
Issue Date | 2019 |
Citation | International Journal of Research in Marketing, 2019, v. 36, n. 2, p. 216-231 How to Cite? |
Abstract | Marketers 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 Identifier | http://hdl.handle.net/10722/302225 |
ISSN | 2023 Impact Factor: 5.9 2023 SCImago Journal Rankings: 3.352 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Li, Xi | - |
dc.contributor.author | Shi, Mengze | - |
dc.contributor.author | Wang, Xin (Shane) | - |
dc.date.accessioned | 2021-08-30T13:58:03Z | - |
dc.date.available | 2021-08-30T13:58:03Z | - |
dc.date.issued | 2019 | - |
dc.identifier.citation | International Journal of Research in Marketing, 2019, v. 36, n. 2, p. 216-231 | - |
dc.identifier.issn | 0167-8116 | - |
dc.identifier.uri | http://hdl.handle.net/10722/302225 | - |
dc.description.abstract | Marketers 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.language | eng | - |
dc.relation.ispartof | International Journal of Research in Marketing | - |
dc.subject | Visual variation | - |
dc.subject | Visual information | - |
dc.subject | Video content | - |
dc.subject | Video mining | - |
dc.title | Video mining: Measuring visual information using automatic methods | - |
dc.type | Article | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1016/j.ijresmar.2019.02.004 | - |
dc.identifier.scopus | eid_2-s2.0-85063268647 | - |
dc.identifier.volume | 36 | - |
dc.identifier.issue | 2 | - |
dc.identifier.spage | 216 | - |
dc.identifier.epage | 231 | - |
dc.identifier.isi | WOS:000474504000004 | - |