Revisiting Algorithmic Audits of TikTok: Poor Reproducibility and Short-term Validity of Findings.
Matej Mosnar|Adam Skurla|Branislav Pecher|Matus Tibensky|Jan Jakubcik|Adrian Bindas|Peter Sakalik|Ivan Srba
| Anthology ID: | DBLP:conf/sigir/MosnarSPTJBSS25 |
|---|---|
| Volume: | Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2025, Padua, Italy, July 13-18, 2025 |
| Year: | 2025 |
| Venue: | Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) |
| Publisher: | ACM |
| Pages: | 3357-3366 |
| URL: | https://doi.org/10.1145/3726302.3730293 |
| DOI: | https://doi.org/10.1145/3726302.3730293 |
| DBLP: | conf/sigir/MosnarSPTJBSS25 |
| BibTeX: |
@inproceedings{mosnar-2025-revisiting,
author = {Matej Mosnar and
Adam Skurla and
Branislav Pecher and
Matus Tibensky and
Jan Jakubcik and
Adrian Bindas and
Peter Sakalik and
Ivan Srba},
editor = {Nicola Ferro and
Maria Maistro and
Gabriella Pasi and
Omar Alonso and
Andrew Trotman and
Suzan Verberne},
title = {{Revisiting Algorithmic Audits of TikTok: Poor Reproducibility and Short-term Validity of Findings}},
booktitle = {{Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2025, Padua, Italy, July 13-18, 2025}},
pages = {3357--3366},
publisher = {ACM},
year = {2025},
url = {https://doi.org/10.1145/3726302.3730293},
doi = {https://doi.org/10.1145/3726302.3730293}
}