The Vicious Cycle of Responding to Negative Comments on Social Media Brand Pages: A Quasi-Experiment with Facebook Policy Change and Machine Learning

Abstract

In the offline world, firms often benefit from responding to consumer complaints. However, the effect of responding to negative comments on social media in the online environment is unclear. A direct firm response may address the negative experience and reduce similar complaints, but such responses are also observable to others engaging with the brand on social media and thus may fuel them to imitate the negative sentiment and complain even more. The authors explore this vicious cycle by analyzing the exogenous Facebook policy change that facilitates firms and users to directly respond to negative comments posted on brand pages. The results indicate that in the wake of Facebook’s revised policy, firms’ responses to negative comments on social media brand pages increase the volume of negative posts and intensify the negative tone directed at firms in the airline, automotive, and hotel industries. This vicious cycle manifests through an “economic” mechanism such that the adverse impact becomes more severe when firms offer financial compensation in their response content on Facebook brand pages. This study contributes to the literature by assessing the impact of firm response to complaints on one of the largest social media platforms, Facebook. Our findings help account for the mixed findings in previous research with respect to the effect of managerial response. In addition, this study introduces a machine learning technique to account for emoticons, linguistic rules, and sentence contexts for unstructured social media data analytics. The findings caution managers against traditional complaint-handling tactics in the new era of social media marketing.

Keywords: social media, social negative word of mouth, policy change, machine learning, management response