摘要
随着互联网和大数据的研究应用日益广泛,对社交网络影响力传播的研究成为数据挖掘和社交网络分析中的热点。从影响力传播模型、影响力传播学习和影响力传播优化3个方面总结了近些年计算机科学领域对影响力传播研究的主要成果,展示了影响力传播研究中对随机模型、数据挖掘、算法优化和博弈论等技术的综合运用。最后,简要讨论了影响力传播研究和应用中存在的问题、挑战及今后的研究方向。
With the wide spread of internet and big data research and applications, influence diffusion research in social network becomes one of the hot topics in data mining and social network analysis in recent years. The main results on social influence diffusion research from the field of computer science in the last decade, which covers the three main areas-- influence diffusion modeling, influence diffusion learning, and influence diffusion optimization, were summarized. Different techniques, such as stochastic modeling, data mining, algorithmic optimization, and game theory, were demonstrated in their application to influence diffusion research. Finally, some discussions on the current issues, challenges and future directions in influence diffusion research and applications were provided.
出处
《大数据》
2015年第3期82-98,共17页
Big Data Research
基金
国家自然科学基金重点项目(No.61433014)~~
关键词
社交网络
社会影响力
影响力传播模型
影响力最大化
社会影响力学习
病毒营销
social network,social influence,influence diffusion model,influence maximization,social influence learning,viral marketing