量化在线公共广场对对抗性操纵策略的脆弱性
Bao Tran Truong1, Xiaodan Lou1, Alessandro Flammini1
1Observatory on Social Media, Indiana University, 1015 E 11th St, Bloomington, IN 47408, USA.
PNAS nexus
|July 12, 2024
概括
社交媒体操纵是一个风险,特别是虚假账户放大虚假信息. 枢纽账户加剧了漏洞,使低质量的内容更容易传播病毒.
科学领域:
- 计算社会科学 计算社会科学
- 网络科学 网络科学
- 信息科学 信息科学 信息科学
背景情况:
- 社交媒体平台容易受到恶意行为者的操纵,他们使用不真实的帐户传播虚假信息.
- 由于数据收集和伦理实验约束,评估这些操作的影响具有挑战性.
研究的目的:
- 量化对抗性操纵策略对在线社区内容质量的影响.
- 确定在传播低质量的内容方面最有效的特定操纵策略.
主要方法:
- 在实证网络上模拟信息传播的社交媒体模型的开发.
- 对抗性操纵对内容质量影响的定量分析.
主要成果:
- 枢纽账户的存在显著增加了社区对操纵的脆弱性.
- 社区透是使低质量的内容传播病毒的最有效策略.
- 用低质量的内容淹没网络会放大伤害,但针对特定的个人会减轻伤害.
结论:
- 社交媒体的结构,特别是枢纽账户,创造了可被虚假信息运动利用的漏洞.
- 社区透等特定策略对于传播错误信息非常有效.
- 有针对性的对策可以增强平台的抗操纵能力,并保护用户.
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