Search for a command to run...
Online brand communities (OBCs) could benefit firms in many usages, ranging from collecting consumers' suggestions or advice to interacting with community members directly and transparently. Creating a positive emotional atmosphere is essential for such communities' healthy development as its boosts the continuous involvement of each member. However, the dynamic cross-influences and evolution of emotions in OBCs have not been fully explored, which was the research gap this paper tried to fill. Based on emotional contagion theory, this study identifies three sources of textual sentiment through machine learning methods in OBCs: member's posts, other members' feedback, and the focal firm's official feedback. This study further tested the dynamic emotional contagion process among these sources on valence (mean) and volatility (dispersion), namely how they affected each other. Data was collected from the MIUI forum, a large forum launched by Xiaomi corporate on August 1, 2011, which contained 17,622 posts and 99,426 feedback. Results showed that: (1) in the emotional contagion process, there existed differences in the influence of emotional valence and volatility from different sources; (2) all emotional interactions were temporary and mostly lasted no more than three days; (3) the most significant contributor of each sources' emotion was itself, which could be explained by lagged effect; (4) the valence of focal firm's emotion (focal firm's official feedback) was the second contributor of the valence of member's emotion (member's posts) and other members' emotion (other members' feedback). Three sources of emotion in OBCs and emotional valence/volatility should be considered when firms try to guide the emotional changes in such communities. Furthermore, firms could proactively influence members' emotions by carefully designing the feedback to members' posts. Besides, since all interactions are temporary, firms need to engage in online communities frequently, like consistently offering feedback.