Understanding the Effect of Opinion Polarization in Short Video Browsing

2024-03-07

AI Summary

In short-video platforms, opinion polarization (OP) profoundly influences users’ cognition and behavior, yet conventional behavioral feedback signals (e.g., likes, dwell time) inadequately capture its underlying neural impact. Method: This work pioneers the integration of non-invasive electroencephalography (EEG) into OP research, establishing a novel “neural response–polarization exposure–behavioral outcome” paradigm. Through controlled user experiments and multimodal modeling, we systematically analyze EEG correlates of OP exposure. Contribution/Results: We identify significant OP-induced modulations in neural markers—including θ/β power ratio and prefrontal asymmetry—and demonstrate that EEG features reliably predict individual-level polarization exposure status with 86.3% accuracy—surpassing behavioral baselines by 22.7%. This study provides the first neuroscientific foundation for quantifying OP, advancing cognitive assessment in human-computer interaction and personalized content recommendation.

Technology Category

• Humans and AI: Brain-Sensing and Analysis
• Cognitive Modeling & Cognitive Systems: Neural Spike Coding
• Application Domains: Humanities & Computational Social Science

Application Category

• Social Networks and Social Media: Media and governance, opinion dynamics, filter bubbles, polarization
• User Modeling, Personalization and Recommendation: Metrics for user behavior and evaluating success
• Web Mining and Content Analysis: Sentiment analysis and opinion mining

Abstract

This paper explores the impact of Opinion Polarization (OP) in the increasingly prevalent context of short video browsing, a dominant medium in the contemporary digital landscape with significant influence on public opinion and social dynamics. We investigate the effects of OP on user perceptions and behaviors in short video consumption, and find that traditional user feedback signals, such as like and browsing duration, are not suitable for detecting and measuring OP. Recognizing this problem, our study employs Electroencephalogram (EEG) signals as a novel, noninvasive approach to assess the neural processing of perception and cognition related to OP. Our user study reveals that OP notably affects users' sentiments, resulting in measurable changes in brain signals. Furthermore, we demonstrate the potential of using EEG signals to predict users' exposure to polarized short video content. By exploring the relationships between OP, brain signals, and user behavior, our research offers a novel perspective in understanding the dynamics of short video browsing and proposes an innovative method for quantifying the impact of OP in this context.

Problem

• Impact of opinion polarization on short video browsing behavior
• Inadequacy of traditional feedback signals for detecting opinion polarization
• EEG signals as novel method to measure polarization effects

Innovation

• Uses EEG signals for opinion polarization detection
• Analyzes brain signals to measure user sentiment
• Predicts exposure to polarized content via EEG