Evaluating Web Domain Credibility: A Multifactorial Score for Analyzing Online Reliability

In a permanently connected society where everyone can share and discuss information of every kind, recognizing credible news or news sources has been demonstrated to be hard. Recent research is going toward the definition of tools that try to automate cognitive processes behind the evaluation of content trustworthiness and simplify people’s lives. However, despite recent efforts to identify fake or misleading content, analyzing sources of information in their entirety remains marginal or only a manual task. This paper aims to define a systematic approach for scoring the credibility of web domains. Specifically, it assesses the Multifactorial Source Credibility Score (MSCS) that, through collecting domain pages as a stream, estimates multiple factors such as the quality of content, the author’s trustworthiness, the presence of biases and advertisements, the source traffic, etc. Then, it evaluates a weighted moving average of web page scores to attribute an overall score to the domain, taking into account scores over time. Through experiments conducted on a real dataset, the study presents promising results by showcasing a notable correlation between the proposed indicator and a manually assigned score by NewsGuard.