The DOI displayed above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
DOI: 10.4121/9ffffc40-9eb6-4eda-a9f0-ad7ebacbd937

Zhang, Weifeng (2023): Relevant Data on the Impact of Visual Elements on Click Behavior When Bilibili (a Chinese social media platform) Users Proactively Search for Popular Science Videos. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/9ffffc40-9eb6-4eda-a9f0-ad7ebacbd937.v1

Usage statistics

Categories

• Communication
• Communication Networks and Services
• Other Information and Communication Services
• Information and Communication Services
• Cultural Understanding

Keywords

Bilibili popular science videos click behavior elaboration likelihood model Visual persuasion

Geolocation

view on openstreetmap

Time coverage

2010-2022

Licence

CC BY 4.0

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by Weifeng Zhang

The data in the EXCEL file consists of statistics and integration of 41,224 video records, including parameters such as blogger name, blogger homepage, number of followers, video links, thumbnail image links, view count, danmaku count, repost count, thumbnail brightness, image quality, color, and other relevant data.

The py file contains the code used in this paper, including data scraping, data cleaning, data visualization, and other processes.

The Brisque algorithm is an image quality assessment algorithm that needs to be implemented using MATLAB software.

History

• 2023-07-25 first online, published, posted

Publisher

4TU.ResearchData

Format

*.xlsx or py

Language

zh-hans

Organizations

School of Journalism and Media, Chongqing Normal University