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Marketing bait (2012) using SMART data to identify e-guanxi among china’s ‘Internet Aborigines’

Chapter


Abstract


  • In this chapter, we present a case study of e-WOM promotion of the action-disaster-horror-thriller film Bait (2012) to understand how geographically dispersed Chinese-speaking fans – representatives of the largest media audience in the world – are using Douban to effectively expand the online cultures of social and commercial film promotion. To achieve this aim, and to discover information that goes beyond the simple browsing of the Douban database, we undertook the beginning stages of sentiment analysis of all 4,348 valid user comments regarding Bait. That is, we conducted word segmentation and dependency analysis on this dataset in order to track the transformative stages undergone by e-WOM in relation to this film. Sentiment analysis (aka opinion mining) uses a combination of machine (system) learning and cloud computing data analysis tools for collecting and distinguishing opinions and attitudes from a source.

Publication Date


  • 2015

Citation


  • Yecies, B., Yang, J., Berryman, M. J. & Soh, K. (2015). Marketing bait (2012) using SMART data to identify e-guanxi among china’s ‘Internet Aborigines’. In N. Mingant, C. Tirtaine & J. Augros (Eds.), Film Marketing into the Twenty-First Century (pp. 132-146). London United Kingdom: British Film Institute - Palgrave. http://www.palgrave.com/page/detail/film-marketing-into-the-twenty-first-century-nolwenn-mingant/?sf1=barcode&st1=9781137443120 2015

Ro Metadata Url


  • http://ro.uow.edu.au/lhapapers/2245

Book Title


  • Film Marketing into the Twenty-First Century

Start Page


  • 132

End Page


  • 146

Place Of Publication


  • London United Kingdom

Abstract


  • In this chapter, we present a case study of e-WOM promotion of the action-disaster-horror-thriller film Bait (2012) to understand how geographically dispersed Chinese-speaking fans – representatives of the largest media audience in the world – are using Douban to effectively expand the online cultures of social and commercial film promotion. To achieve this aim, and to discover information that goes beyond the simple browsing of the Douban database, we undertook the beginning stages of sentiment analysis of all 4,348 valid user comments regarding Bait. That is, we conducted word segmentation and dependency analysis on this dataset in order to track the transformative stages undergone by e-WOM in relation to this film. Sentiment analysis (aka opinion mining) uses a combination of machine (system) learning and cloud computing data analysis tools for collecting and distinguishing opinions and attitudes from a source.

Publication Date


  • 2015

Citation


  • Yecies, B., Yang, J., Berryman, M. J. & Soh, K. (2015). Marketing bait (2012) using SMART data to identify e-guanxi among china’s ‘Internet Aborigines’. In N. Mingant, C. Tirtaine & J. Augros (Eds.), Film Marketing into the Twenty-First Century (pp. 132-146). London United Kingdom: British Film Institute - Palgrave. http://www.palgrave.com/page/detail/film-marketing-into-the-twenty-first-century-nolwenn-mingant/?sf1=barcode&st1=9781137443120 2015

Ro Metadata Url


  • http://ro.uow.edu.au/lhapapers/2245

Book Title


  • Film Marketing into the Twenty-First Century

Start Page


  • 132

End Page


  • 146

Place Of Publication


  • London United Kingdom