一种基于独立级联模型和在线社交网络中趋势搜索列表的热门话题传播方法
Yuqi Chen1, Xianyong Li1, Weikai Zhou1
1School of Computer and Software Engineering, Xihua University, Chengdu 610039, China.
Mathematical biosciences and engineering : MBE
|June 16, 2023
概括
这项研究引入了一种新模型,用于预测在线网络中热门话题的传播,提高了对现有方法的准确性. ICTSL模型分析用户行为和趋势搜索,以更好地预测趋势.
科学领域:
- 社交网络分析 社交网络分析
- 信息传播建模 信息传播建模
- 计算社会科学 计算社会科学
背景情况:
- 在线社交网络促进了信息的快速传播.
- 预测流行话题的传播对于理解在线动态至关重要.
- 现有的模型可能无法完全捕捉受趋势搜索列表影响的扩散.
研究的目的:
- 预测在线社交网络中热门话题的传播趋势.
- 开发一种包含用户特征和趋势搜索数据的新型传播模型.
- 评估拟议模型的预测性能与既有方法相比.
主要方法:
- 建议的用户传播意愿,怀疑程度,主题贡献,主题受欢迎程度和新用户数量.
- 开发了独立布与趋势搜索列表 (ICTSL) 模型.
- 使用独立级联 (IC) 模型作为基线进行比较.
主要成果:
- 该ICTSL模型与实际话题传播数据显示出高度一致性.
- 与IC,ICPB,CCIC和二级IC模型相比,ICTSL模型实现了0.78%-3.71%的平均平方误差减少.
- 实验结果验证了模型在三个现实世界的热门话题中的有效性.
结论:
- 拟议的ICTSL模型为预测热门话题传播提供了更准确的方法.
- 结合趋势搜索列表和用户特定因素可以提高扩散预测.
- ICTSL模型为分析和预测在线社交网络中传播的信息提供了有价值的工具.
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