报告题目：Using User- and Marketer-Generated Content for Box-Office Revenue Prediction: Differences between Micro-Blogging and Third-Party Platforms
报告人：宋婷婷 助理教授
邀请人：闵庆飞 教授
时间：2019年11月14日（周四），下午2:00-4:00
地点：经济管理学院D区212
报告摘要：
In this research, we build a prediction model of movie box office revenue by empirically exploring its intricate relationships with user-generated content (UGC) as well as marketer-generated content (MGC) on a microblogging platform and UGC on a third-party platform. Our analyses are based on a panel vector autoregression (PVAR) model that is calibrated with a combination of data from Weibo (microblogging platform) and Douban! Movies (third party). Our empirical results show that microblogging UGC (MUGC) is a significant predictor of box office revenue and has stronger predictive power than UGC on Douban! Movies (DUGC). In addition, we find that the volume of enterprise microblogs (i.e., MGC) predicts box office revenue directly and also indirectly via MUGC, and MUGC thus exerts a partial mediating effect on the predictive relationship between the volume of enterprise microblogs and box office revenue. Finally, a prediction model of box office revenue using lagged box office revenue, MGC, MUGC, and DUGC is proposed, and its forecasting accuracy is found to outperform that of existing models. Managerial implications on utilizing social media for enterprises are provided.
人物简介：
宋婷婷，上海交通大学安泰经济与管理学院管理信息系统系助理教授，清华大学经济与管理学院管理科学与工程系博士，研究兴趣包括：社会化媒体、用户生成内容、社会网络关系、电子商务等，其研究发表于Information Systems Research （ISR）以及Information and Management （I&M）上，曾获得中国信息经济学2019优秀成果奖。
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