Abstract

Understanding how humans evaluate credibility is an important scientific question in the era of fake news. Message credibility is among crucial aspects of credibility evaluations. One of the most direct ways to understand message credibility is to use measurements of brain activity of humans performing credibility evaluations. Nevertheless, message credibility has never been investigated using such a method before. This article reports the results of an experiment during which we have measured brain activity during message credibility evaluation, using EEG. The experiment allowed for identification of brain areas that were active when participant made positive or negative message credibility evaluations. Based on experimental data, we modeled and predicted human message credibility evaluations using EEG brain activity measurements with F1 score exceeding 0.7.

Highlights

  • The World Wide Web has been designed for low barriers of entry, enabling fast, and cheap publication of content

  • We describe an experiment that enables the study of message credibility evaluation without prior knowledge, and with perfect knowledge

  • The results reported here regarding differences in brain activity during message credibility evaluation with and without prior knowledge are missing in the pilot study (Kawiak et al, 2020)

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Summary

Introduction

The World Wide Web has been designed for low barriers of entry, enabling fast, and cheap publication of content. The prevalent business model of the web provides high incentives for producing Web content that impacts opinions and beliefs of Web users. These commercial incentives are caused by the popularity of Web-based marketing and advertising. Web content affects not just our shopping decisions, and decisions regarding our health, or politics. In this technical and economic environment, the spread of fake news has become an increasingly significant social problem (Sharma et al, 2019). Fake news disseminate through social media, Web-based newspapers, blogs, and regular Web pages

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