WhichTok？对比三种TikTok数据采集工具
WhichTok? Comparing Three TikTok Data Acquisition Tools
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中文总结 AI 辅助
本研究系统对比TikTok Research API、Pyktok和Apify三种数据采集工具，发现它们在话题标签等端点存在显著差异，仅用户端点结果一致，据此提出提升TikTok研究质量的相关建议。
中文摘要 AI 辅助
TikTok的全球增长使其成为娱乐和政治话语的主要平台，推动了社会科学研究的增加。然而，这个快速发展的研究领域面临着根本性的可重复性危机。TikTok不透明的算法系统阻碍研究人员得出有意义的实证推断，而标准化数据收集方法的缺乏加剧了这些挑战。本研究通过系统对比三种数据采集工具——官方TikTok Research API、Pyktok和Apify，解决这些方法学缺口。我们评估了五个端点：用户（User）、话题标签（Hashtag）、关键词（Keyword）、评论（Comment）和相关视频（Related Video）。结果显示存在显著的跨工具差异，尤其是在话题标签和关键词搜索方面。Research API使用后端API调用，而Apify和Pyktok依赖前端网页抓取，在检索内容所代表的时间段和流行度水平上产生系统性差异。三种工具仅在用户端点产生全面且一致的结果。我们的结果质疑这些工具是否能获取真正的随机样本，因为它们引入了可能以尚未完全理解的方式损害研究有效性的方法学混淆因素。基于这些结果，我们提供方法学、透明度和伦理方面的建议与指南，以提高TikTok研究的质量。
英文摘要
TikTok's global growth has made it a prime platform for both entertainment and political discourse, prompting increased social science research. However, this rapidly evolving research field faces a fundamental reproducibility crisis. TikTok's opaque algorithmic systems hinder researchers from drawing meaningful empirical inferences, while the lack of standardized data collection methods compounds these challenges. This study addresses these methodological gaps by systematically comparing three data collection tools - the official TikTok Research API, Pyktok, and Apify. We evaluated five endpoints: User, Hashtag, Keyword, Comment, and Related Video. Results show substantial cross-tool differences, especially for hashtag and keyword searches. The Research API uses back-end API calls, whereas Apify and Pyktok rely on front-end web scraping, producing systematic differences in the time periods and popularity levels represented in retrieved content. The three tools yielded comprehensive and consistent results only for the user endpoint. Our results question whether these tools can acquire truly random[-ized] samples, as they introduce methodological confounds that may compromise research validity in ways not yet fully understood. Based on these results, we offer methodological, transparency, and ethical recommendations and guidelines to increase TikTok research quality.
