Modeling MGC Strategies under Extreme Negative UGC


Jiayin Qi
Qixing Qu
Yong Tan
Jifeng Mu


The impact of user-generated content (UGC), especially extreme negative UGC (EN_UGC) on firms is well recognized. Moreover, insightful qualitative marketer-generated content (MGC) strategies have been proposed to respond to negative UGC. However, few quantitative and analytical modeling studies have been conducted to explore the effectiveness of each proposed strategies under different scenarios to counteract EN_UGC. This research aims to explore optimal MGC strategies for firms to handle EN_UGC by proposing an EN_UGC propagation model based on MGC and EN_UGC interaction. We provide the runaway mode and effective mode in handling EN_UGC. Our results show that in runaway mode, MGC does not affect the propagation of EN_UGC, and the optimal MGC strategy is to do nothing. However, in effective mode, the effect strength of MGC on EN_UGC is the most important key factor in defending against EN_UGC propagation, followed by the input rate of the subgroup where users accept and repost MGC. Based on our model, we also explain why MGC strategies such as deleting post and employing paid posters are helpless in EN_UGC’s management. Overall, the findings in this research offer some unique implications for UGC management.

Key Word: 

Published Date: 

August, 2014

Full File: