🤖 AI Summary
This study addresses the tendency of conventional recommendation algorithms to over-optimize user engagement, thereby exacerbating information cocoons—a problem further compounded by existing approaches that often neglect human cognitive limitations and lack practical implementability. To counter this, the authors propose the Agenda Democratization Index (ADI) and a Social Information Health (SIH) model, introducing a domain-selective bridging strategy that integrates user engagement with cross-group bridging directly into the algorithmic scoring function. Bridging weights are dynamically adjusted based on the variability of information domains and their collective influence, enabling domain-adaptive optimization of bridging intensity. This work reframes the information cocoon challenge as a computationally tractable engineering design problem. Multi-agent simulations demonstrate that, compared to uniform bridging strategies, the proposed approach effectively enhances the sharing of collective-decision-related information while preserving user experience in interest- and lifestyle-oriented domains.
📝 Abstract
Echo chambers are an inevitable consequence of the human cognitive system being evolutionarily designed to prioritize processing of high-relevance information at the small-group scale, combined with algorithms that optimize engagement as their sole objective. Conventional prescriptions that normatively criticize echo chambers and demand individual behavioral change have low feasibility given these cognitive constraints. This paper constructs an Agenda Democratization Index (ADI) that quantities the decentralization of agenda-setting power using four variables barrier to entry, granularity, interactivity, and feedback resolution and a SocialInformation Health (SIH) model that integrates ADI with the strength of bridging mechanisms. Based on this model, we propose domain-selective bridging, which incorporates not only engagement but also bridging into algorithmic scoring functions, optimizing the bridging weight for each information domain based on variability (V ) and collective scope (S). An agent-based simulation comparing three algorithm designs no bridging, uniform bridging, and domain-selective bridging demonstrated that domain-selective bridging substantially outperforms uniform bridging on a joint efficiency measure (SIH user satisfaction) by a factor whose absolute value is sensitive to Model 1's near-zero user satisfaction, but whose direction and dominance ranking are robust improving information sharing in domains relevant to collective decision-making while maintaining user experience in hobby and lifestyle domains. This paper reframes the echo chamber debate from a normative opposition over whether to eliminate echo chambers to an engineer-ing design problem of in which information domains, to what degree, and through what algorithm design should bridging be implemented.