摘要
人类日常行为活动在生活的各个方面普遍存在。个体行为活动类型多样且个体之间行为差异明显,人类行为显示出高度复杂性。利用微博用户发布微博所产生的时间数据来研究用户的时间行为模式,研究发现个体用户时间间隔的统计特征主要服从幂律、指数和双模3种分布函数;并提出了基于任务队列的个体用户行为动力学模型,解释了用户发布微博的时间间隔分布特征。
Human daily activities are widespread in all aspects of life. Human behavior has the characteristics of high complexity because of its various types of individual activities and individual differences. Using microblog users＇ microblogging time data, we studied the time behavior of users. The results show that the statistical characteristics of time interval for individual users mainly follow three distributions： power-law, exponential and bimodal distribution. Further- more, we proposed an individual behavior dynamic model based on task queue to explain the characteristics of time interval for the microblog users.
出处
《计算机科学》
CSCD
北大核心
2016年第6期24-27,共4页
Computer Science
关键词
人类行为
时间统计特性
微博
行为模式
Human behaviors, Time statistical properties, Microblogs, Behavior patterns
