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

Author

Listed:
  • Qiang Zhang

    (School of Management and Economics and Shenzhen Finance Institute, The Chinese University of Hong Kong, Shenzhen (CUHK-Shenzhen), 518172 Shenzhen, China)

  • Wenbo Wang

    (Department of Marketing, Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong)

  • Yuxin Chen

    (Stern School of Business, New York University, New York, New York 10012)

Abstract

Consumption of entertainment products such as movies, video games, and sports events often lasts 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 and 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 viewers’ 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 (i.e., camera motion, shot length, sound loudness, pitch, and spoken lines). We demonstrate that MTMS significantly predicts viewers’ postconsumption appreciation of movies and that it can be evaluated at a finer level to identify engaging content. Finally, we discuss the information value of MTMS with the presence of measures used in the previous literature and the value of integrating supply-side content information into in-consumption analysis.

Suggested Citation

  • Qiang Zhang & Wenbo Wang & Yuxin Chen, 2020. "Frontiers: In-Consumption Social Listening with Moment-to-Moment Unstructured Data: The Case of Movie Appreciation and Live Comments," Marketing Science, INFORMS, vol. 39(2), pages 285-295, March.
  • Handle: RePEc:inm:ormksc:v:39:y:2020:i:2:p:285-295
    DOI: 10.1287/mksc.2019.1215
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    References listed on IDEAS

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    Cited by:

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    4. Jiayue Liu & Ziyao Zhou & Ming Gao & Jiafu Tang & Weiguo Fan, 2023. "Aspect sentiment mining of short bullet screen comments from online TV series," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 74(8), pages 1026-1045, August.
    5. Zecong Ma & Sergio Palacios, 2021. "Image-mining: exploring the impact of video content on the success of crowdfunding," Journal of Marketing Analytics, Palgrave Macmillan, vol. 9(4), pages 265-285, December.
    6. Jordi McKenzie, 2023. "The economics of movies (revisited): A survey of recent literature," Journal of Economic Surveys, Wiley Blackwell, vol. 37(2), pages 480-525, April.
    7. Shasha Lu & Hye-Jin Kim & Yinghui Zhou & Li Xiao & Min Ding, 2022. "Audio and Visual Analytics in Marketing and Artificial Empathy," Foundations and Trends(R) in Marketing, now publishers, vol. 16(4), pages 422-493, April.
    8. Liu, Zhenyuan & Geng, Ruoqi & Tse, Ying Kei (Mike) & Han, Shuihua, 2023. "Mapping the relationship between social media usage and organizational performance: A meta-analysis," Technological Forecasting and Social Change, Elsevier, vol. 187(C).

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