Can temporal article-level credibility signals improve domain-level credibility prediction?

2026-07-05

AI Summary

This study addresses the challenge of assessing the credibility of emerging web domains that lack historical reputation, rendering traditional evaluation methods ineffective. To overcome this limitation, the authors propose the Domain Credibility Evaluation Framework (DCEF), which, for the first time, leverages temporal sequences of article-level credibility signals within a domain to emulate the judgment logic of professional fact-checkers and automatically predict the overall trustworthiness of previously unseen domains. Built upon expert-annotated data, DCEF employs time-series modeling and aggregates article-level credibility scores into an end-to-end automated assessment system. Experimental results demonstrate that domain-level credibility can be effectively predicted using only article content, establishing a novel paradigm and a practical pathway for evaluating the trustworthiness of emerging domains.

Abstract

Web domain credibility evaluation is vital for combating misinformation. It is conducted by examining factors such as domain type, transparency, and overall reputation. However, assessing the credibility of newly emerging web domains remains challenging since they have no reputation yet. Expert fact-checkers evaluate the credibility of domains by analyzing the content of their articles, including the presence of misinformation, bias, or propaganda. Yet, the ease of large-scale content generation enabled by LLMs has accelerated the creation of new content, rendering manual assessment insufficient and underscoring the need for automated approaches to domain credibility evaluation. In this paper, we introduce our Domain Credibility Evaluation Framework (DCEF), a temporal framework for domain credibility evaluation grounded in expert ratings. DCEF enables us to investigate whether the credibility of web domains can be assessed from their published articles following the workflow of expert fact-checkers, without any prior knowledge of the source domains themselves.

Problem

• domain credibility
• misinformation
• temporal signals
• fact-checking
• web domains

Innovation

• temporal credibility signals
• domain credibility evaluation
• automated fact-checking
• article-level analysis
• LLM-generated content