The proliferation of social media not only enables users to produce original contents, but also brings plenty of copycatting opportunities. The copying behavior over online user-generated content (UGC) can impact content originators by diverting the potential content returns (e.g., likes and retweets). To maintain the originators’ incentive of producing original contents, it is necessary for social platforms to develop targeted punishment and compensation regulations based on the diverted returns. Thus, this study proposes to explore and measure the diversion process of content consumer returns. To formulate the returns diversion caused by copycats, a Diversion-Aware Bass model (DA-Bass) is developed by introducing the substitute effect and collaborative effect. The role of content originality in the diffusion process is further estimated. Experiments have been conducted to demonstrate the proposed model’s effectiveness in supporting social platforms to trace and measure the diverted returns.


Paper Number 1161; Track Cybersecurity; Short Paper


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