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


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
Issue number5
StatePublished - 2017

Bibliographical note

Funding Information:
This work was supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea (NRF-2014S1A5A2A01013756 and NRF-2016S1A5A2A01025553) and Hongik University Research Fund.

Publisher Copyright:
Copyright © 2017 Inderscience Enterprises Ltd.


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


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