We present an approach for the prediction of user authorship and feedback behavior with shared content. We consider that users use models of other users and their feedback to choose what to publish next. We look at the problem as a game between authors and audiences and relate it to current content-based user modeling solutions with no prior strategic models. As applications, we consider the large-scale authorship of Wikipedia pages, movies and food recipes. We demonstrate analytic properties, authorship and feedback prediction results, and an overall framework to study content authorship regularities in social media.

中文翻译：

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作为作者-观众游戏的社交媒体

我们提出了一种使用共享内容预测用户作者和反馈行为的方法。我们认为用户使用其他用户的模型和他们的反馈来选择下一步要发布的内容。我们将问题视为作者和观众之间的游戏，并将其与当前基于内容的用户建模解决方案相关联，而无需事先制定战略模型。作为应用程序，我们考虑了维基百科页面、电影和食物食谱的大规模作者身份。我们展示了分析特性、作者和反馈预测结果，以及研究社交媒体内容作者规律的整体框架。