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Previous research has studied interactive value formation (IVF) using resource- or practice-based approaches but has neglected the role of emotions. This article aims to show how emotions are correlated in problematic social media interactions and explore their role in IVF.

By combining a text mining algorithm, nonparametric Spearman's rho and thematic qualitative analysis in an explanatory sequential mixed-method design, the authors (1) categorize customers' comments as positive, neutral or negative; (2) pinpoint peaks of negative comments; (3) classify problematic interactions as detrimental, contradictory or conflictual; (4) identify customers' main positive (joy, trust and surprise) and negative emotions (anger, dissatisfaction, disgust, fear and sadness) and (5) correlate these emotions.

Despite several problematic social interactions, the same pattern of emotions appears but with different intensities. Additionally, value co-creation, value no-creation and value co-destruction co-occur in a context of problematic social interactions (peak of negative comments).

This study provides new insights into the effect of customers' emotions during IVF by studying the links between positive and negative emotions and their effects on different sorts of problematic social interactions.