摘要
微博已经成为日常生活中最流行的信息分享工具.转发是微博中信息传播的核心方法,所以转发量预测不仅是一个有趣的研究问题,也有较大的实际意义.然而,当前大部分研究只是把问题视为分类或回归问题,没有考虑转发的传播过程.本文中,我们提出一个符合转发传播过程的转发量预测模型.本文认为转发信息来自两方面:直接粉丝和间接粉丝,而粉丝带来的转发量由转发意愿和影响力决定.我们用历史行为和内容相关性来估算一名直接粉丝的转发意愿,并用他/她的影响力来估算通过他/她的间接粉丝的转发量.新浪微博上的实验表明我们的模型比其他已有的方法效果好.
Micro-blog has become the most popular information sharing tool in our daily life. The retweet behavior is a main method of information propagation in micro-biog. So the retweet number prediction is an interesting research topic and has much practical significance. However, most of current researches only regard this problem as aclassification or re- gression problem, and they did not consider the retweet propagation process. Considering the retweet propagation process, we propose a retweet number prediction model BCI. In our model, we think retweet messages are from two parts, direct follow- ers and indirect followers. The retweet number of followers is decided by their retweet intention and influence. We use be- havior and content information to estimate retweet intention for a direct follower and use the influence to estimate the indirect followers＇ retweet number. Experimental results on Sina Weibo dataset show that our retweet number prediction model has much better performance than other well-established methods.
出处
《电子学报》
EI
CAS
CSCD
北大核心
2016年第12期2989-2996,共8页
Acta Electronica Sinica
基金
国家重点基础研究发展计划(No.2013CB329606)
国家自然科学基金(No.61375058
No.71231002)
北京市高等教育青年英才项目
关键词
转发量预测
转发意愿
转发影响力
retweet number prediction
retweet intention
the influence on retweeting
