社交媒体机器人和人类特征的全球比较
Lynnette Hui Xian Ng1, Kathleen M Carley2
1Center for Computational Analysis of Social and Organizational Systems, Societal and Software Systems Carnegie Mellon University, Pittsburgh, PA, 15213, USA. lynnetteng@cmu.edu.
Scientific reports
|March 31, 2025
概括
社交媒体机器人占聊天的20%,在沟通风格,结构和身份呈现方面与人类不同. 了解这些区别是检测和管理机器人在线活动的关键.
科学领域:
- 计算社会科学 计算社会科学
- 人工智能的人工智能
- 网络安全 网络安全
背景情况:
- 社交媒体平台越来越多地由自动化帐户或机器人以及人类用户组成.
- 机器人可以传播虚假信息并操纵在线叙述,造成重大网络安全风险.
- 现有的机器人定义通常是特定于事件的,需要更基本的,第一原则的定义.
研究的目的:
- 开发一个普遍的,第一原则定义的社交媒体机器人.
- 在全球事件中系统地比较机器人和人类的通信特征.
- 探索机器人作为人工智能算法的进化潜力.
主要方法:
- 分析了来自7个全球事件的约2亿用户的社交媒体推特.
- 语言线索的比较,内容身份对齐以及机器人和人类之间的交互结构.
- 开发了一个精细的定义:"社交媒体机器人是一个自动化帐户,它在社交媒体平台上执行一系列机制,用于内容创建,分发和收集,以及/或关系形成和解散.
主要成果:
- 机器人占社交媒体聊天的20%,与人类不同的沟通模式.
- 机器人表现出自动化的语言线索 (例如,标签,积极术语) 和星互动结构.
- 人类显示对话理解线索 (例如,回复) 和层次的交互结构,与不那么明显的身份内容对齐.
结论:
- 机器人和人类在他们的在线沟通,机器人检测和交互模式方面表现出根本的差异.
- 提供了关于机器人使用,监管和未来研究方向的建议.
- 关键的挑战包括检测,区分和破坏恶意机器人,同时保持人类对话.
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