The influence of firm's feedbacks on user-generated content's linguistic style matching-An explanation based on...

In virtual brand communities, users and firms continuously use different or similar linguistic styles to communicate with each other. Existing literature has demonstrated that the linguistic style matching (LSM) between the coming users' posts [user-generated content (UGC)] and existing firms' content will influence users' behavior, like promoting users to release more posts. However, little research has been conducted to analyze how firms' feedbacking behaviors influence LSM. To fill the gap, this paper uses Python to measure the LSM between 69,463 posts from 9,777 users and existing firms' generated content in the MIUI community and examines the impact of firms' feedbacks on this LSM. The results show that the firms' feedbacks frequency increased the LSM, but the firms' feedbacks text length decreased the LSM. In addition, users' textual sentiment and the published text length moderate the impact of firms' feedbacks (e.g., frequency, text length) on LSM. Specifically, the users' textual sentiment valence increases the positive effect of firms' feedbacks frequency and weakens the negative effect of firms' feedbacks text length on LSM. The users' produced content text length reduced the positive effect of firms' feedbacks frequency and offset the negative effect of the firms' feedbacks text length on LSM. Further, the effects above are significant for the relatively active users but not for the inactive ones. Based on communication accommodation theory, this paper investigates the impact of firms' feedbacks frequency and text length on subsequent users' posting behaviors, providing an essential reference for guiding firms' virtual brand community management.