How people utilise tweets on movie selection? the reverse effects of e-WoM valence on movie sales

Hyunjeong Kang, Sangmi Chai, Hyong Uk Kim

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

The volume of big data being generated by social network sites (SNS) is increasing significantly. This study seeks to identify the marketapplicable insights concerning the text-type big data generated by SNS and to suggest market reaction strategies for responding to signals emerging from big data. Since people can instantly access large amount of online word-of-mouth (e-WoM) contents due to mobile communications, movie sales are influenced significantly from various SNS contents. Based on this phenomenon, we focused on Twitter, one of the most prevalent micro-blogging services. This research conducted a sentiment analysis to determine consumer valences regarding products. This study finds that the extremity of sentiment -as measured by growth speed in the number of positive or negative tweets -changed the direction of the tweets, positive or negative effect on revenue regardless of the valence of the word-of-mouth. The implication for SNS marketing professionals will be discussed.

Original languageEnglish
Pages (from-to)537-553
Number of pages17
JournalInternational Journal of Mobile Communications
Volume15
Issue number5
DOIs
StatePublished - 2017

Keywords

  • analytics
  • big data
  • mobile communications
  • sentiment
  • SNS
  • Twitter
  • valence
  • word-of-mouth

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