ML Anthology

Data Void Exploits: Tracking & Mitigation Strategies (Extended Abstract)

Miro Mannino, Junior Garcia, Reem Hazim, Azza Abouzied, Paolo Papotti
IJCAI 2025 pp. 10927-10931
doi:10.24963/IJCAI.2025/1218 /ijcai/2025/mannino2025ijcai-data/

Abstract

In the evolving landscape of online information, disinformation is a growing concern. A concept central to this challenge is the "data void", a situation where there is a lack of relevant information online regarding certain search terms. This creates an opportunity for misleading or false narratives to fill the gap, often influencing public perception. In this work, we present methods to track and mitigate data voids in Web search settings.

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Cite

Text

Mannino et al. "Data Void Exploits: Tracking & Mitigation Strategies (Extended Abstract)." International Joint Conference on Artificial Intelligence, 2025. doi:10.24963/IJCAI.2025/1218

Markdown

[Mannino et al. "Data Void Exploits: Tracking & Mitigation Strategies (Extended Abstract)." International Joint Conference on Artificial Intelligence, 2025.](https://mlanthology.org/ijcai/2025/mannino2025ijcai-data/) doi:10.24963/IJCAI.2025/1218

BibTeX

@inproceedings{mannino2025ijcai-data,
  title     = {{Data Void Exploits: Tracking & Mitigation Strategies (Extended Abstract)}},
  author    = {Mannino, Miro and Garcia, Junior and Hazim, Reem and Abouzied, Azza and Papotti, Paolo},
  booktitle = {International Joint Conference on Artificial Intelligence},
  year      = {2025},
  pages     = {10927-10931},
  doi       = {10.24963/IJCAI.2025/1218},
  url       = {https://mlanthology.org/ijcai/2025/mannino2025ijcai-data/}
}