利用影子禁令塑造社交网络中的观点
Shaping Opinions in Social Networks with Shadow Banning
AI总结：
提出基于优化的影子禁令方法，可在大规模社交网络上将观点塑造成期望分布，并揭示其可能被平台隐蔽滥用以操纵观点。
摘要：
社交网络上有害内容和错误信息的泛滥，要求实施内容审核政策以维护平台健康。其中一种政策是影子禁令，它限制了内容的可见性。影子禁令的危险在于，社交媒体平台可能滥用它来操纵观点。在此，我们提出一种基于优化的影子禁令方法，能够将观点塑造成期望的分布，并可扩展到大型网络。在真实网络拓扑上的模拟表明，我们的影子禁令策略能够改变观点，并增加或减少观点极化。我们发现，如果以将观点朝特定方向移动为目标进行影子禁令，所产生的影子禁令策略可能看起来是中性的。这表明社交媒体平台有可能在未被察觉的情况下滥用影子禁令。我们的结果展示了影子禁令在社交网络中进行观点操纵的威力与危险。
英文摘要：
The proliferation of harmful content and misinformation on social networks necessitates content moderation policies to maintain platform health. One such policy is shadow banning, which limits content visibility. The danger of shadow banning is that it can be misused by social media platforms to manipulate opinions. Here we present an optimization based approach to shadow banning that can shape opinions into a desired distribution and scale to large networks. Simulations on real network topologies show that our shadow banning policies can shift opinions and increase or decrease opinion polarization. We find that if one shadow bans with the aim of shifting opinions in a certain direction, the resulting shadow banning policy can appear neutral. This shows the potential for social media platforms to misuse shadow banning without being detected. Our results demonstrate the power and danger of shadow banning for opinion manipulation in social networks.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
