Social media and the diffusion of an information technology product

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The expansion of the Internet has led to a huge amount of information posted by consumers online through social media platforms such as forums, blogs, and product reviews. This study proposes a diffusion model that accommodates pre-launch social media information and combines it with post-launch sales information in the Bass model to improve the accuracy of sales forecasts. The model is characterized as the extended Bass model, with time varying parameters whose evolutions are affected by the consumer’s communications in social media. Specifically, we construct variables from social media by using sentiment analysis and topic analysis. These variables are fed as key parameters in the diffusion model’s evolution process for the purpose of plugging the gap between the time-invariant key parameter model and that of observed sales. An empirical study of the first-generation iPhone during 2006 and 2007 shows that the model using additional variables extracted from sentiment and topic analysis on BBS performs best based on several criteria, including DIC (Deviance Information Criteria), marginal likelihood, and forecasting errors of holdout samples. We discuss the role of social media information in the diffusion process for this study.

Original languageEnglish
Title of host publicationKnowledge and Systems Sciences, 19th International Symposium, KSS 2018, Proceedings
EditorsJian Chen, Mina Ryoke, Yuji Yamada, Xijin Tang
PublisherSpringer
Pages171-185
Number of pages15
ISBN (Print)9789811331480
DOIs
Publication statusPublished - 2018 Jan 1
Event19th International Symposium on Knowledge and Systems Sciences, KSS 2018 - Tokyo, Japan
Duration: 2018 Nov 252018 Nov 27

Publication series

NameCommunications in Computer and Information Science
Volume949
ISSN (Print)1865-0929
ISSN (Electronic)1865-0937

Conference

Conference19th International Symposium on Knowledge and Systems Sciences, KSS 2018
CountryJapan
CityTokyo
Period18/11/2518/11/27

Keywords

  • Bass model
  • Diffusion
  • Hierarchical Bayes model Predictive density
  • Sentiment analysis Time varying parameter
  • Social media data
  • Text analysis
  • Topic model

ASJC Scopus subject areas

  • Computer Science(all)
  • Mathematics(all)

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