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Bridging Systems: Open Problems for Countering Destructive Divisiveness across Ranking, Recommenders, and Governance

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arxiv 2301.09976 v3 pith:Y5NN5VOT submitted 2023-01-24 cs.SI

classification cs.SI
keywords bridgingsystemsacrossalgorithmscapacitydeliberationdivisivenessdomains
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Divisiveness appears to be increasing in much of the world, leading to concern about political violence and a decreasing capacity to collaboratively address large-scale societal challenges. In this working paper we aim to articulate an interdisciplinary research and practice area focused on what we call bridging systems: systems which increase mutual understanding and trust across divides, creating space for productive conflict, deliberation, or cooperation. We give examples of bridging systems across three domains: recommender systems on social media, collective response systems, and human-facilitated group deliberation. We argue that these examples can be more meaningfully understood as processes for attention-allocation (as opposed to "content distribution" or "amplification") and develop a corresponding framework to explore similarities - and opportunities for bridging - across these seemingly disparate domains. We focus particularly on the potential of bridging-based ranking to bring the benefits of offline bridging into spaces which are already governed by algorithms. Throughout, we suggest research directions that could improve our capacity to incorporate bridging into a world increasingly mediated by algorithms and artificial intelligence.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. OpenAlex reports about 19 citations worldwide. Full citation record

  1. Re-ranking Using Large Language Models for Mitigating Exposure to Harmful Content on Social Media Platforms

    cs.CL 2025-01 conditional novelty 5.0 of 10

    LLM pairwise re-ranking of recommendation sequences reduces simulated harmful-content exposure more than Perspective API and OpenAI Moderation API, in zero-shot and few-shot settings.

  2. AI and the Future of Digital Public Squares

    cs.CY 2024-12 unverdicted novelty 3.0 of 10

    A multi-stakeholder agenda argues that LLM-enabled collective dialogue, bridging, moderation, and proof-of-humanity tools can strengthen digital public squares if paired with research and safeguards.

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