中文脑肿瘤相关短视频在TikTok和Bilibili上的传播、质量与可靠性分析：横断面研究表4

数据集获取（Figshare）

• 源站标题：Table_4_Analyzing dissemination, quality, and reliability of Chinese brain tumor-related short videos on TikTok and Bilibili: a cross-sectional study.XLSX
• DOI：10.3389/fneur.2024.1404038.s004
• 发布日期：2024-10-18
• 文件数：1 个
• 文件总体积：9.04 KB
• 源站页面：https://frontiersin.figshare.com/articles/dataset/Table_4_Analyzing_dissemination_quality_and_reliability_of_Chinese_brain_tumor-related_short_videos_on_TikTok_and_Bilibili_a_cross-sectional_study_XLSX/27253701

命令行下载

curl -L -o "Table_4_Analyzing dissemination, quality, and reliability of Chinese brain tumor-related short videos on TikTok and Bilibili: a cross-sectional study.XLSX" "https://ndownloader.figshare.com/files/49857774"

文件清单

• Table_4_Analyzing dissemination, quality, and reliability of Chinese brain tumor-related short videos on TikTok and Bilibili: a cross-sectional study.XLSX（9.04 KB）

文件总体积 9.04 KB（源站 API 实测）。

数据加载示例（图像类）

from PIL import Image
import glob, os

files = (glob.glob(os.path.join(path, "**", "*.png"), recursive=True)
       + glob.glob(os.path.join(path, "**", "*.jpg"), recursive=True)
       + glob.glob(os.path.join(path, "**", "*.tif"), recursive=True))
print("图像文件数:", len(files))
img = Image.open(files[0]); print("尺寸/模式:", img.size, img.mode)

# torchvision Dataset 方式:
# from torchvision import datasets
# ds = datasets.ImageFolder(path)  # 要求 子目录=类别

目录组织与标注格式以源站说明和下载后实际文件为准。

数据说明

BackgroundAs the Internet becomes an increasingly vital source of medical information, the quality and reliability of brain tumor-related short videos on platforms such as TikTok and Bilibili have not been adequately evaluated. Therefore, this study aims to assess these aspects and explore the factors influencing the dissemination of such videos.
MethodsA cross-sectional analysis was conducted on the top 100 brain tumor-related short videos from TikTok and Bilibili. The videos were evaluated using the Global Quality Score and the DISCERN reliability instrument. An eXtreme Gradient Boosting algorithm was utilized to predict dissemination outcomes. The videos were also categorized by content type and uploader.
ResultsTikTok videos scored relatively higher on both the Global Quality Score (median 2, interquartile range [2, 3] on TikTok vs. median 2, interquartile range [1, 2] on Bilibili, p = 1.51E-04) and the DISCERN reliability instrument (median 15, interquartile range [13, 18.25] on TikTok vs. 13.5, interquartile range [11, 16] on Bilibili, p = 1.66E-04). Subgroup analysis revealed that videos uploaded by professional individuals and institutions had higher quality and reliability compared to those uploaded by non-professional entities. Videos focusing on disease knowledge exhibited the highest quality and reliability compared to other content types. The number of followers emerged as the most important variable in our dissemination prediction model.
ConclusionThe overall quality and reliability of brain tumor-related short videos on TikTok and Bilibili were unsatisfactory and did not significantly influence video dissemination. Future research should expand the scope to better understand the factors driving the dissemination of medical-themed videos.

许可

CC BY 4.0

引用

学术使用请引用 DOI 10.3389/fneur.2024.1404038.s004（source: https://frontiersin.figshare.com/articles/dataset/Table_4_Analyzing_dissemination_quality_and_reliability_of_Chinese_brain_tumor-related_short_videos_on_TikTok_and_Bilibili_a_cross-sectional_study_XLSX/27253701）。