A framework for visualizing and describing city image promotion short video data based on microcube model DOI Creative Commons

Jing He,

Z. W. Yang, Jiayi Zhu

и другие.

PLoS ONE, Год журнала: 2025, Номер 20(4), С. e0317883 - e0317883

Опубликована: Апрель 10, 2025

Background The rapid development of media technology and environment provides rich resources convenient ways to shape the image city. Short video has become an important help city build brand. How use short is key link urban construction. This study focuses on six primary variables for analyzing videos: unexpected events, emotional resonance, scene transition, elemental amplification, element interaction, screen style. These were selected based their demonstrated impact engagement dissemination efficiency. In order realize comprehensive analysis content, collected 20,668 screenshots from Douyin platform as data samples. Data collection spanned July 2019 December 2019, was conducted using Python programming language with Pandas Matplotlib libraries processing visualization. Objective To reveal relationship between content features popularity by quantitative visual methods, provide reference optimizing brand promotion strategies. Conclusion (1) microcube model shows strong flexibility applicability in analysis, can complex characteristics communication effect. (2) Unexpected events resonance are factors attractiveness effect videos. Reasonable design switching interaction significantly enhances

Язык: Английский

A framework for visualizing and describing city image promotion short video data based on microcube model DOI Creative Commons

Jing He,

Z. W. Yang, Jiayi Zhu

и другие.

PLoS ONE, Год журнала: 2025, Номер 20(4), С. e0317883 - e0317883

Опубликована: Апрель 10, 2025

Background The rapid development of media technology and environment provides rich resources convenient ways to shape the image city. Short video has become an important help city build brand. How use short is key link urban construction. This study focuses on six primary variables for analyzing videos: unexpected events, emotional resonance, scene transition, elemental amplification, element interaction, screen style. These were selected based their demonstrated impact engagement dissemination efficiency. In order realize comprehensive analysis content, collected 20,668 screenshots from Douyin platform as data samples. Data collection spanned July 2019 December 2019, was conducted using Python programming language with Pandas Matplotlib libraries processing visualization. Objective To reveal relationship between content features popularity by quantitative visual methods, provide reference optimizing brand promotion strategies. Conclusion (1) microcube model shows strong flexibility applicability in analysis, can complex characteristics communication effect. (2) Unexpected events resonance are factors attractiveness effect videos. Reasonable design switching interaction significantly enhances

Язык: Английский

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