【报告人简介】

Zaruhi Hakobyan，卢森堡大学研究员、慕尼黑CESifo兼职研究员，获莫斯科高等经济学院理论经济学系以及卢森堡大学卢森堡金融学院博士学位。研究领域为信息经济学、网络与动态博弈，主要探讨经济理论中的信息、策略互动和网络如何塑造经济决策与结果等问题。

【内容摘要】

Recommendation systems determine more than what users see: amplifying a source can also make that source a more important reference point for others. This creates a challenge for accuracy-oriented regulation because the exposure patterns that best promote truth tracking need not coincide with those preferred by users or favored by engagement incentives. We study this tension in a network coordination model in which users observe public and private information, have heterogeneous directional biases, and value coordination with others. Feed composition therefore affects two margins simultaneously: it changes information exposure and the coordination weight placed on recommended sources. We characterize source selection under an accuracy mandate and show that neither informativeness nor a source's own bias is sufficient to determine whom to amplify. Optimal ranking trades off information gains against the network-wide distortion generated by additional coordination influence. We then identify two limits to accuracy-oriented design. First, network design can reduce directional distortion but cannot generally eliminate it completely. Second, accuracy-improving changes need not be privately implementable when users control their exposure. This conflict persists even under complete information: every unilateral cross-cutting reallocation of coordination weight away from an echo chamber raises truth-tracking accuracy while lowering the deviating user's utility. An engagement-oriented platform can reinforce this tension by favoring more validating exposure patterns at the expense of accuracy. The results distinguish information delivery, coordination influence, and user adoption as separate margins of platform design.

【更多信息】

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撰稿：王杰 审核：崔惠玉 单位：高等经济研究院