在社交媒体上建模信息传播:以数据为导向的观察
Adriana Iamnitchi1, Lawrence O Hall2, Sameera Horawalavithana2
1Department of Advanced Computing Sciences, Institute of Data Science, Maastricht University, Maastricht, Netherlands.
Frontiers in big data
|June 2, 2023
概括
由于现实世界的事件和平台算法,模拟在线信息传播具有挑战性. 这项研究分享了国防高级研究项目署 (DARPA) 的SocialSim计划关于模拟社会行为和信息演变的教训.
科学领域:
- 计算社会科学 计算社会科学
- 信息科学 信息科学 信息科学
- 网络科学 网络科学
背景情况:
- 在社交媒体上模拟信息传播对于理解受众的接触和打击错误信息至关重要.
- 现实世界的事件,协调活动和平台算法使准确的信息传播建模复杂化.
研究的目的:
- 为了记录从国防高级研究项目署 (DARPA) SocialSim计划中学到的经验教训.
- 为在线社会行为的高保真计算模拟的未来研究提供信息,特别是信息传播和进化.
主要方法:
- 在DARPA SocialSim计划中的研究工作.
- 分析使用真实世界数据建模信息传播的挑战.
主要成果:
- 确定了准确建模信息传播的重大挑战.
- 突出了外部事件,影响力活动和平台算法对信息传播的影响.
结论:
- 分享实践经验和从4年多的研究项目中学到的经验教训.
- 提供洞察力,以帮助其他在计算社会模拟中开展类似项目的研究人员.
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