Business intelligence from user generated content

online opinion formation in purchasing decisions in high-tech markets

Karan Setiya, Jolien Ubacht, Scott Cunningham, Sertac Oruc

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

1 Citation (Scopus)

Abstract

User Generated Content (UGC) requires new business intelligence methods to understand the influence of online opinion formation on customer purchasing decisions. We developed a conceptual model for deriving business intelligence from tweets, based on the Classical Model of Consensus Formation and the Theory of Planned Behaviour. We applied the model to the dynamic high-tech smartphone market by means of three case studies on the launch of new smartphones. By using Poisson regression, data- and sentiment-analysis on tweets we show how opinion leadership and real-life events effect the volume of online chatter and sentiments about the launch of new smartphones. Application of the model reveals businesses parameters that can be influenced to enhance competitiveness in dynamic high tech markets. Our conceptual model is suitable to be turned into a predictive model that takes the richness of tweets in online opinion formation into account.
Original languageEnglish
Title of host publicationLecture Notes in Computer Science
Subtitle of host publicationConference on e-Business, e-Services and e-Society
Place of PublicationCham
PublisherSpringer
Pages505-521
Number of pages17
Volume9844
ISBN (Print)9783319452333
DOIs
Publication statusPublished - 13 Sep 2016
Event15th IFIP WG 6.11 Conference on e-Business, e-Services, and e-Society, I3E 2016 - Swansea, United Kingdom
Duration: 13 Sep 201615 Sep 2016

Conference

Conference15th IFIP WG 6.11 Conference on e-Business, e-Services, and e-Society, I3E 2016
Abbreviated title3E 2016
CountryUnited Kingdom
CitySwansea
Period13/09/1615/09/16

Fingerprint

opinion formation
Competitive intelligence
Purchasing
Smartphones
market
predictive model
competitiveness
customer
leadership
regression
event

Keywords

  • business intelligence
  • user generated content
  • Twitter
  • sentiment analysis
  • opinion formation
  • smartphones
  • high-tech markets

Cite this

Setiya, K., Ubacht, J., Cunningham, S., & Oruc, S. (2016). Business intelligence from user generated content: online opinion formation in purchasing decisions in high-tech markets. In Lecture Notes in Computer Science : Conference on e-Business, e-Services and e-Society (Vol. 9844, pp. 505-521). Cham: Springer. https://doi.org/10.1007/978-3-319-45234-0_45
Setiya, Karan ; Ubacht, Jolien ; Cunningham, Scott ; Oruc, Sertac. / Business intelligence from user generated content : online opinion formation in purchasing decisions in high-tech markets. Lecture Notes in Computer Science : Conference on e-Business, e-Services and e-Society. Vol. 9844 Cham : Springer, 2016. pp. 505-521
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Setiya, K, Ubacht, J, Cunningham, S & Oruc, S 2016, Business intelligence from user generated content: online opinion formation in purchasing decisions in high-tech markets. in Lecture Notes in Computer Science : Conference on e-Business, e-Services and e-Society. vol. 9844, Springer, Cham, pp. 505-521, 15th IFIP WG 6.11 Conference on e-Business, e-Services, and e-Society, I3E 2016, Swansea, United Kingdom, 13/09/16. https://doi.org/10.1007/978-3-319-45234-0_45

Business intelligence from user generated content : online opinion formation in purchasing decisions in high-tech markets. / Setiya, Karan; Ubacht, Jolien; Cunningham, Scott; Oruc, Sertac.

Lecture Notes in Computer Science : Conference on e-Business, e-Services and e-Society. Vol. 9844 Cham : Springer, 2016. p. 505-521.

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

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Setiya K, Ubacht J, Cunningham S, Oruc S. Business intelligence from user generated content: online opinion formation in purchasing decisions in high-tech markets. In Lecture Notes in Computer Science : Conference on e-Business, e-Services and e-Society. Vol. 9844. Cham: Springer. 2016. p. 505-521 https://doi.org/10.1007/978-3-319-45234-0_45