Schneider Piotr, Wójcik Grzegorz M, Kawiak Andrzej, Kwasniewicz Lukasz, Wierzbicki Adam
Department of Neuroinformatics and Biomedical Engineering, Institute of Computer Science, Maria Curie-Sklodowska University, Lublin, Poland.
Polish-Japanese Academy of Information Technology, Warsaw, Poland.
Front Hum Neurosci. 2022 May 6;16:808382. doi: 10.3389/fnhum.2022.808382. eCollection 2022.
Understanding how humans evaluate credibility is an important scientific question in the era of fake news. Source credibility is among the most important aspects of credibility evaluations. One of the most direct ways to understand source credibility is to use measurements of brain activity of humans who make credibility evaluations. This article reports the results of an experiment during which we have measured brain activity during credibility evaluation using EEG. In the experiment, participants had to learn source credibility of fictitious students based on a preparatory stage, during which they evaluated message credibility with perfect knowledge. The experiment allowed for identification of brain areas that were active when a participant made positive or negative source credibility evaluations. Based on experimental data, we modeled and predicted human source credibility evaluations using EEG brain activity measurements with F1 score exceeding 0.7 (using 10-fold cross-validation). We are also able to model and predict message credibility evaluations with perfect knowledge, and to compare both models obtained from a single experiment.
在假新闻盛行的时代，了解人类如何评估可信度是一个重要的科学问题。来源可信度是可信度评估中最重要的方面之一。理解来源可信度最直接的方法之一是测量进行可信度评估的人的大脑活动。本文报告了一项实验的结果，在该实验中我们使用脑电图（EEG）测量了可信度评估过程中的大脑活动。在实验中，参与者必须在一个准备阶段之后了解虚构学生的来源可信度，在这个准备阶段他们在完全知晓的情况下评估信息可信度。该实验能够识别参与者进行正面或负面来源可信度评估时活跃的脑区。基于实验数据，我们使用脑电图大脑活动测量对人类来源可信度评估进行建模和预测，F1分数超过0.7（使用10折交叉验证）。我们还能够对完全知晓情况下的信息可信度评估进行建模和预测，并比较从单个实验中获得的两个模型。
