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Business Intelligence from User Generated Content: Online Opinion Formation in Purchasing Decisions in High-Tech Markets

机译:用户生成内容的商业智能:高科技市场中购买决策的在线意见形成

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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.
机译:用户生成的内容(UGC)需要新的商业智能方法,以了解在线意见形成对客户购买决策的影响。我们基于共识形成的经典模型和计划行为理论,开发了从推文中获取商业智能的概念模型。通过针对新智能手机发布的三个案例研究,我们将该模型应用于了动态的高科技智能手机市场。通过在推特上使用Poisson回归,数据和情感分析,我们展示了意见领袖和现实事件如何影响在线聊天量和有关新智能手机发布的情感。该模型的应用揭示了可以受到影响以增强在动态高科技市场中的竞争力的业务参数。我们的概念模型适合转变为一种预测模型,该模型考虑了在线意见形成过程中推文的丰富性。

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