Abstract
YouTube has become one of the most influential channels in recent years. There are an enormous number of videos on the platform, but few of them are popular, getting placed in the “Trending” section. But, videos on this list have different stories. Some of them will get constant popularity and others will fade out. Many researchers have analyzed what will make a video become popular. However, no study has focused on how long a video maintains its popularity. In addition, the content similarity between the thumbnail image and the title has been neglected, although it appears to play an important role in social media posts (e.g. blogs, Instagram). We measure the variable, content similarity, by analyzing the thumbnail image and text. This study investigates the impact of this new variable on popular videos’ survival to give YouTubers and advertisers insights into video marketing. Also, our suggested approach can achieve new academic results in the research of YouTube.
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References
Argyris, Y.E.A., Xu, J.D.: Influencer marketing for increasing consumer engagement and brand connection. Commun. Assoc. Inf. Syst. 34, 555–585 (2018)
Figueiredo, F., Benevenuto, F., Almeida, J.M.: The tube over time: characterizing popularity growth of YouTube videos. In: Proceedings of the fourth ACM International Conference on Web Search and Data Mining, pp. 745–754 (2011)
Fontanini, G., Bertini, M., Del Bimbo, A.: Web video popularity prediction using sentiment and content visual features. In: Proceedings of the 2016 ACM on International Conference on Multimedia Retrieval, pp. 289–292 (2016)
Fu, W.W.: Selecting online videos from graphics, text, and view counts: the moderation of popularity bandwagons. J. Comput. Mediated Commun. 18(1), 46–61 (2012)
Holland, M.: How YouTube developed into a successful platform for user-generated content. Elon J. Undergrad. Res. Commun., 7(1) (2016)
Jiang, L., Miao, Y., Yang, Y., Lan, Z., Hauptmann, A.G.: Viral video style: a closer look at viral videos on YouTube. In: Proceedings of ACM International Conference on Multimedia Retrieval, p. 193 (2014)
Joglekar, S., Sastry, N., Redi, M.: Like at first sight: understanding user engagement with the world of microvideos. In: Ciampaglia, G.L., Mashhadi, A., Yasseri, T. (eds.) SocInfo 2017. LNCS, vol. 10539, pp. 237–256. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-67217-5_15
Mitchell, V.L.: Knowledge integration and information technology project performance. Mis Q. 30, 919–939 (2006)
Richier, C., Altman, E., Elazouzi, R., Altman, T., Linares, G., Portilla, Y.: Modelling view-count dynamics in YouTube. arXiv preprint arXiv:1404.2570 (2014)
Shin, D., He, S., Lee, G.M., Whinston, A.B., Cetintas, S., Lee, K.C.: Enhancing social media analysis with visual analytics: a deep learning approach (2017)
Tucker, C.E.: The reach and persuasiveness of viral video ads. Mark. Sci. 34(2), 281–296 (2014)
Yu, H., Xie, L., Sanner, S.: The lifecycle of a YouTube video: phases, content and popularity, pp. 533–542. ICWSM (2015)
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Choe, M.G., Park, J.H., Seo, D.W. (2019). How Long Will Your Videos Remain Popular? Empirical Study of the Impact of Video Features on YouTube Trending Using Deep Learning Methodologies. In: Xu, J., Zhu, B., Liu, X., Shaw, M., Zhang, H., Fan, M. (eds) The Ecosystem of e-Business: Technologies, Stakeholders, and Connections. WEB 2018. Lecture Notes in Business Information Processing, vol 357. Springer, Cham. https://doi.org/10.1007/978-3-030-22784-5_19
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DOI: https://doi.org/10.1007/978-3-030-22784-5_19
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