To better understand how big data interconnects firms and customers, we analyse the role of customers’ emotions in the process of value co-destruction in a social media context. We perform a text mining based algorithm capable of identifying anger, expectation, disgust, fear, and sadness in peaks of problematic social interactions. The developed algorithm associated with an in-depth qualitative analysis shows how to employ unstructured big data to understand
the role of negative emotions in the process of value co-destruction
