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• W2736353946 abstract "Customer experience management (CEM) in the social media age finds itself needing to adapt to a rapidly changing digital environment and hence there is a need for innovative digital data analytical solutions. Drawing on an action case study of a large global automotive manufacturer, this study presents a digital innovation for enhanced emotion analytics on user generated content (UGC) and behaviour (UGB), to improve consumer insights for CEM. The digital innovation captures customer experience in real time, enabling measurement of a wide range of discrete emotions on the studied social media platform, which goes beyond traditional tools that capture positive or negative sentiment only. During the digital intervention, a substantial number of inauthentic and bot like behaviours was revealed, unbeknown to the case organisation. These accounts were found to be posting and amplifying highly emotional and potentially damaging content surrounding the case brand and its products. The study illustrates how emotion in the context of customer experience should go beyond typical categorisations, given the complexity of human emotion, while a distinction between bot and authentic users is imperative for CEM." @default.
• W2736353946 created "2017-07-31" @default.
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• W2736353946 date "2017-09-01" @default.
• W2736353946 modified "2023-10-16" @default.
• W2736353946 title "Big data opportunities for social behavioral and mental health research" @default.
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• W2736353946 doi "https://doi.org/10.1016/j.socscimed.2017.07.018" @default.
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