UPCOMING EVENTS

Extracting and utilizing in-consumption moment-to-moment dynamics: The case of movie appreciation and live comments

2019-04-10
Date: 2019-04-18 15:29:51
Time: 10:00-12:00
Venue: Alumni Center
Speaker: Yuxin Chen
Category: Talk & Lecture

Venue: Xixi Hall, 1st floor, Alumni Center, Zijingang Campus

Speaker: Yuxin Chen is the Dean of Business and the Distinguished Global Professor of Business at NYU Shanghai, with an affiliation with Stern School of Business, New York University. Prior to NYU Shanghai, Dr. Chen was the Polk Brothers Professor of Retailing and Professor of Marketing at the Kellogg School of Management at Northwestern University and was a tenure professor at NYU Stern. The primary research interests of Dr. Chen include data-driven marketing, Internet marketing, pricing, retailing, competitive strategies, structural empirical models, Bayesian econometric methods, behavioral economics, and marketing in emerging markets.   Dr. Chen received his B.S. in Physics from Fudan University, a MSBA and a Ph.D. in Marketing from Washington University in St. Louis. He also studied in Computer Science department in the Graduate School of Zhejiang University.  

Abstract:

This research develops a new approach for in-consumption social listening and demonstrates its value in the context of online movie watching wherein viewers can react to movie content with live comments. Specifically, we propose a novel measure, moment-to-moment synchronicity (MTMS), to capture consumers’ in-consumption engagement. MTMS refers to the synchronicity between temporal variations in the volume of live comments and those in movie content mined from unstructured video, audio, and text data from movies. We demonstrate that MTMS has a significant impact on viewers’ post-consumption appreciation of movies, and it can be evaluated at finer level to identify engaging content. Finally, we discuss the relation between MTMS and existing in-consumption measures and the value of integrating supply-side content information into in-consumption analysis.