[论文解读] Strategic Expression, Popularity Traps, and Welfare in Social Media

Zafer Kanik, Zaruhi Hakobyan|arXiv (Cornell University)|Jan 4, 2026

Opinion Dynamics and Social Influence被引用 0

一句话总结

该论文在社交媒体上建立了一个功利主义的战略表达模型，其中人气激励影响发帖与曝光，揭示状态相关的福利效应与新颖的人气陷阱。

ABSTRACT

Social media platforms systematically reward popularity over authenticity, incentivizing users to strategically tailor their expression for attention. In this paper, we introduce (i) popularity as a strategic expression mechanism, distinct from the canonical mechanisms of conformity, learning, persuasion, and (mis)information transmission in social networks, and (ii) a utilitarian framework for measuring user welfare that maps directly to observable platform metrics, filling a critical gap in the social media literature. In the model, agents hold fixed heterogeneous authentic opinions and derive utility gains from the popularity of their own posts -- measured by likes received, and utility gains (losses) from exposure to content that aligns with (diverges from) their authentic opinion. Social media interaction acts as a state-dependent welfare amplifier: light topics generate Pareto improvements, whereas intense topics make everyone worse off in a polarized society (e.g., political debates during elections). Moreover, strategic expression amplifies social media polarization during polarized events while dampening it during unified events (e.g., national celebrations). Consequently, strategic distortions magnify welfare outcomes, expanding aggregate gains in light topics while exacerbating losses in intense, polarized ones. Counterintuitively, strategic agents often face a popularity trap: posting a more popular opinion is individually optimal, yet collective action by similar agents eliminates their authentic opinion from the platform, leaving them worse off than under the authentic-expression benchmark. Homophilic algorithms that match users with preferred content -- widely used by platforms -- discipline popularity-driven behavior, narrowing the popularity trap region and limiting its welfare effects.

研究动机与目标

• 研究在社交媒体上人气驱动的表达如何与固定的真实意见交互并产生影响。
• 建立一个功利主义框架，将发帖与曝光与可观察的指标（如点赞）联系起来。
• 分析在不同社会状态下的福利含义（轻话题与强话题；极化与统一事件）。
• 描述相较于自给自足与真实表达基准，战略表达如何重塑意见频率和福利。

提出的方法

• 定义一个具有固定真实意见和定向粉丝网络的代表性社媒环境。
• 形式化代理人效用，包含人气、对齐收益和错位成本等组成部分（方程式 1）。
• 证明均衡发帖属于已实现的意见集合，而非新意见（命题 1）。
• 专设到三意见空间（-b, 0, +b）以研究极化与福利（第4节）。
• 推导在何种条件下社媒放大或抑制极化（命题 2）。
• 在均衡与自给自足及真实表达基准下评估福利，包括对人气陷阱的讨论（第5节）。

实验结果

研究问题

• RQ1 人气激励是否导致战略性发帖，从而改变社媒上意见分布？
• RQ2 在不同话题强度和极化水平下，战略表达相对于自给自足与真实表达对福利有何影响？
• RQ3 在三意见情境下，社媒在何种条件下放大或抑制社会极化（与统一）？
• RQ4 对具有真实意见的个体而言，人气陷阱的性质与范围为何？
• RQ5 网络密度与算法筛选如何影响这些福利与极化效应？

主要发现

• 发帖收敛于已实现的意见集合；任何均衡发帖都不落在已实现意见之间（命题 1）。
• 社媒可以是一个依状态而定的福利放大器：在轻话题下通常提高福利，但在强烈、极化的话题下会降低福利。
• 在高极化事件中极化被放大，在低极化事件中被抑制，前提是存在策略性发帖（命题 2）。
• 出现一种称为“人气陷阱”的机制：发帖一个更受欢迎的意见反而可能降低个体的真实表达与福利。
• 基于偏好的算法或同类暴露可以缩小人气陷阱并限制福利效应。