Business intelligence from user generated content: online opinion formation in purchasing decisions in high-tech markets

Karan Setiya; Jolien Ubacht; Scott Cunningham; Sertac Oruc

doi:10.1007/978-3-319-45234-0_45

Business intelligence from user generated content: online opinion formation in purchasing decisions in high-tech markets

Karan Setiya, Jolien Ubacht, Scott Cunningham, Sertac Oruc

Politics

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution book

1 Citation (Scopus)

23 Downloads (Pure)

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 language	English
Title of host publication	Lecture Notes in Computer Science
Subtitle of host publication	Conference on e-Business, e-Services and e-Society
Place of Publication	Cham
Publisher	Springer
Pages	505-521
Number of pages	17
Volume	9844
ISBN (Print)	9783319452333
DOIs	https://doi.org/10.1007/978-3-319-45234-0_45
Publication status	Published - 13 Sept 2016
Event	15th IFIP WG 6.11 Conference on e-Business, e-Services, and e-Society, I3E 2016 - Swansea, United Kingdom Duration: 13 Sept 2016 → 15 Sept 2016

Conference

Conference	15th IFIP WG 6.11 Conference on e-Business, e-Services, and e-Society, I3E 2016
Abbreviated title	3E 2016
Country/Territory	United Kingdom
City	Swansea
Period	13/09/16 → 15/09/16

Keywords

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

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10.1007/978-3-319-45234-0_45Licence: Unspecified

Setiya-etal-LNCS2016-Business-intelligence-user-generated-content-online-opinion-formation-purchasingAccepted author manuscript, 936 KBLicence: CC BY 4.0

Cite this

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title = "Business intelligence from user generated content: online opinion formation in purchasing decisions in high-tech markets",

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.",

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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 et al.
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 proceeding › Conference contribution book

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T1 - Business intelligence from user generated content

T2 - 15th IFIP WG 6.11 Conference on e-Business, e-Services, and e-Society, I3E 2016

AU - Setiya, Karan

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AU - Oruc, Sertac

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N2 - 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.

AB - 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.

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KW - opinion formation

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ER -

Business intelligence from user generated content: online opinion formation in purchasing decisions in high-tech markets

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