July 27, 2025

A Data-Driven Approach to Supporting Fact-Checking and Mitigating Mis/Disinformation Through Domain Quality Evaluation

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Machine-learning approach assesses trustworthiness of domains to improve fact-checking and mitigate misinformation.

This study presents a machine-learning system for evaluating the trustworthiness of domains to address misinformation.
A dataset of expert-rated domains is utilized to predict credibility scores, achieving a mean absolute error of 0.12.
Feature importance analysis reveals that PageRank-based features significantly enhance trustworthiness predictions.
The scalable design enables continuous assessments of thousands of domains, improving the efficiency of verification efforts.

Mohammadmosaferi et al. (2025) studied this question.

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