Self-directed online information search can affect policy attitudes: a randomized encouragement design with digital behavioral data

2025-01-06

AI Summary

This study investigates how online information seeking causally influences public policy attitudes under information overload. Using a randomized incentivized experiment with 791 German participants, it passively tracked real-world search behavior on three policy issues—childcare, renewable energy transition, and cannabis legalization—and linked these behavioral traces to validated attitude scales and fine-grained behavioral pattern analysis. Methodologically, it innovatively integrates naturalistic passive tracking with experimental randomization, substantially enhancing ecological validity. A key contribution is the identification of policy-specific “granularity characteristics”—notably value-conflict intensity and technical complexity—as critical moderators of informational influence. Results show that information seeking significantly shifts attitudes toward childcare and cannabis legalization, but exerts no detectable effect on renewable energy attitudes. Crucially, search-topic focus and dwell time per page emerge as the strongest behavioral predictors of attitude change.

Technology Category

• Application Domains: Humanities & Computational Social Science
• Search and Optimization: Learning to Search
• Natural Language Processing: Information Extraction

Application Category

• User Modeling, Personalization and Recommendation: Attacks and countermeasures in recommendation systems
• Web Mining and Content Analysis: Content-based information diffusion
• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems

Abstract

The abundance of information sources in our digital environment makes it difficult to study how such information shapes individuals' attitudes towards current policies. Our study investigates how self-directed online search in a naturalistic setting through three randomized controlled experiments with 791 German participants on three topical policy issues: basic child support, renewable energy transition, and cannabis legalization. Participants' online browsing was passively tracked, and changes in their attitudes were measured. By encouraging participants to seek online information, this study enhances ecological validity compared to traditional experiments that expose subjects to predetermined content. Significant attitude shifts were observed for child support and cannabis legalization, but not for renewable energy transition. Some findings suggest that the specificity and granularity of policy topics may affect whether and how online information shapes political views, providing insights into the nuanced impact of online information seeking on policy attitudes. By exploring participant's searches and visits, we depict the behavioral patterns that emerge on from our encouragement. Our experimental approach lays the groundwork for future research to advance understanding of the media effect within the dynamic online information landscape.

Problem

• Information Influence
• Public Opinion
• Policy Perception

Innovation

• Public Policy Attitudes
• Online Information Seeking
• Behavioral Patterns Analysis