Selective exposure to online news occurs when users favor information that confirms their beliefs, creating filter bubbles and limiting diverse perspectives. Interactive systems can counter this by recommending different perspectives, but to achieve this, they need a real-time metric for selective exposure. We present an experiment where we evaluate Electroencephalography (EEG) and eye tracking as indicators for selective exposure by using eye tracking to recognize which textual parts participants read and using EEG to quantify the magnitude of selective exposure. Participants read online news while we collected EEG and eye movements with their agreement towards the news. We show that the agreement with news correlates positively with the theta band power in the parietal area. Our results indicate that future interactive systems can sense selective exposure using EEG and eye tracking to propose a more balanced information diet. This work presents an integrated experimental setup that identifies selective exposure using gaze and EEG-based metrics.

翻译：在线新闻阅读中的选择性接触现象指用户倾向于选择符合自身信念的信息，从而形成信息茧房并限制多元视角。交互系统可通过推荐不同观点来应对此问题，但需要实时度量选择性接触的指标。本研究设计了一项实验，通过眼动追踪识别被试阅读的文本区域，并利用脑电图量化选择性接触程度，从而评估脑电与眼动作为选择性接触指标的可行性。在参与者阅读在线新闻时，我们同步采集其脑电信号与眼动数据，并记录其对新闻内容的认同度。实验结果表明，对新闻的认同度与顶叶区θ频段功率呈正相关。研究结论显示，未来的交互系统可借助脑电与眼动技术感知选择性接触行为，从而为用户提供更均衡的信息供给。本工作提出了一种融合眼动与脑电指标的实验框架，能够有效识别选择性接触现象。