【公开学术报告】In-Consumption Social Listening with Moment-to-Moment Unstructured Data: The Case of Movie Appreciation and Live Comments

Topic: In-Consumption Social Listening with Moment-to-Moment Unstructured Data: The Case of Movie Appreciation and Live Comments

Date & Time: 9:30-11:00am, Mon. 12^th, November 2018

Venue: Room 2101, Tongji Building A

Language: English

Speaker：Dr. Qiang ZHANG (Hong Kong University of Science and Technology)

ABSTRACT

Consumption of entertainment products, such as movies, video games, and sports events, takes place over a nontrivial time period. During these experiences, consumers are likely to encounter temporal variations in the content of consumption, to which they may react in real time. Compared with existing in-consumption analysis (e.g., eye tracking, neural activity analysis), listening to in-consumption consumers’ voices on social media has great potential. Our paper proposes 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 to listen to the live comments through 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 (i.e., camera motion, shot length, sound loudness, pitch, and spoken lines). 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.

Keywords: moment-to-moment data, unstructured data, social listening, live comments, consumption experience, online movie streaming