# Unveiling News Publishers Trustworthiness Through Social Interactions

arXiv: https://arxiv.org/abs/2402.18621 · HTML: https://mlsanity.com/paper/2402.18621/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 28 Feb 2024.

## Built on by (most cited first, 1 of 1)

- [Yesterday's News: Benchmarking Multi-Dimensional Out-of-Distribution Generalization of Misinformation Detection Models](https://mlsanity.com/paper/2410.18122/) (2024)

## Abstract (arXiv)

With the primary goal of raising readers' awareness of misinformation phenomena, extensive efforts have been made by both academic institutions and independent organizations to develop methodologies for assessing the trustworthiness of online news publishers. Unfortunately, existing approaches are costly and face critical scalability challenges. This study presents a novel framework for assessing the trustworthiness of online news publishers using user interactions on social media platforms. The proposed methodology provides a versatile solution that serves the dual purpose of i) identifying verifiable online publishers and ii) automatically performing an initial estimation of the trustworthiness of previously unclassified online news outlets.