Research on the influence of Chinese film Weibo topics on film success based on sentiment time curve and clustering

Weijing Huang; Yong Huang; Jinjiang Yan

doi:10.1117/12.3009369

11 October 2023 Research on the influence of Chinese film Weibo topics on film success based on sentiment time curve and clustering

Weijing Huang, Yong Huang, Jinjiang Yan

Author Affiliations +

Proceedings Volume 12918, Fourth International Conference on Computer Science and Communication Technology (ICCSCT 2023); 129180E (2023) https://doi.org/10.1117/12.3009369
Event: International Conference on Computer Science and Communication Technology (ICCSCT 2023), 2023, Wuhan, China

Abstract

Public film review is an important reference standard for film quality evaluation. 67.9% of users in China choose to use Weibo to share their personal film-watching feelings, and more than 80% of users say that word of mouth about a film on Weibo is easy to influence their film-watching behavior. This paper collected 236,011 Weibo topic data of 41 Chinese films in 2022. Sentiment time curve clustering model is used to explore the influence of sentiment changes on consumers’ film preferences and thus on film success. By combining the competitive distance measurement method and the partitioning algorithm, this paper selects the K-shape+SBD method with the best profile coefficient performance to cluster the sentiment time series data, and then the study found that the Weibo topic text clustering of 41 Chinese films was divided into four categories, showing four trends of “M-type”, “slowly descending”, “forward-inverted V-type” and “slowly rising” respectively. The changing trend of sentiment will significantly affect the success of films. Films with “slowly rising” are more likely to achieve commercial and word-of-mouth success, “M-type” and “forward-inverted V-type” are more likely to achieve better word-of-mouth, and “forward-inverted V-type” can attract more users to post film reviews.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

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Weijing Huang, Yong Huang, and Jinjiang Yan "Research on the influence of Chinese film Weibo topics on film success based on sentiment time curve and clustering", Proc. SPIE 12918, Fourth International Conference on Computer Science and Communication Technology (ICCSCT 2023), 129180E (11 October 2023); https://doi.org/10.1117/12.3009369

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KEYWORDS

Associative arrays

Web 2.0 technologies

Distance measurement

Data modeling

Analytical research

Matrices

Reflection

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