Navigating the Post-API Dilemma
Amrit Poudel, Tim Weninger
摘要
Recent decisions to discontinue access to social media APIs are having detrimental effects on Internet research and the field of computational social science as a whole. This lack of access to data has been dubbed the Post-API era of Internet research. Fortunately, popular search engines have the means to crawl, capture, and surface social media data on their Search Engine Results Pages (SERP) if provided the proper search query, and may provide a solution to this dilemma. In the present work we ask: does SERP provide a complete and unbiased sample of social media data? Is SERP a viable alternative to direct APIaccess? To answer these questions, we perform a comparative analysis between (Google) SERP results and nonsampled data from Reddit and Twitter/X. We find that SERP results are highly biased in favor of popular posts; against political, pornographic, and vulgar posts; are more positive in their sentiment; and have large topical gaps. Overall, we conclude that SERP is not a viable alternative to social media API access. This paper has been published in the proceedings of WWW 2024. Please cite it accordingly. This paper contains material that may not be suitable for all audiences. Reader discretion is advised.
问问这篇 Paper
智能体会读完全文。
Lune 把这篇 Paper 索引到了每一个公式,引用它的顶会 Paper 也一样。你提问,回答直接引用原文。
引用它的顶会 Paper3
- Citations and Trust in LLM Generated ResponsesYifan Ding, Matthew Facciani, Ellen Joyce, Amrit Poudel 等AAAI 2025 · 被引用 9 次
- Digital Gatekeepers: Google's Role in Curating Hashtags and SubredditsAmrit Poudel, Yifan Ding, Tim Weninger, Jürgen PfefferACL 2025 · 被引用 1 次
- "Please don't send that bot anything": A Mixed-methods Study of Personal Impersonation Attacks Targeting Digital Payments on Social MediaHoang Dai Nguyen, Sumit Dhungana, Madhulika Itha, Phani VadrevuUSENIX Security 2025
相关 Paper
- Post-Post-API Age: Studying Digital Platforms in Scant Data Access TimesKayo Mimizuka, Megan A. Brown, Kai-Cheng Yang, Josephine LukitoCSCW 2026 · 被引用 1 次
- Subjective Crowd Disagreements for Subjective Data: Uncovering Meaningful CrowdOpinion with Population-level LearningTharindu Cyril Weerasooriya, Sarah Luger, Saloni Poddar, Ashiqur R. KhudaBukhsh 等ACL 2023 · 被引用 2 次
- Having your Privacy Cake and Eating it Too: Platform-supported Auditing of Social Media Algorithms for Public InterestBasileal Imana, Aleksandra Korolova, John S. HeidemannCSCW 2023 · 被引用 18 次
- Media Source Matters More Than Content: Unveiling Political Bias in LLM-Generated CitationsSunhao Dai, Zhanshuo Cao, Wenjie Wang, Liang Pang 等EMNLP 2025
- Neural Retrievers are Biased Towards LLM-Generated ContentSunhao Dai, Yuqi Zhou, Liang Pang, Weihao Liu 等KDD 2024 · 被引用 26 次
