基于行为分析的微博信息传播效果

发布时间：2018-05-12 20:31

本文选题：微博 + 行为预测　；参考：《计算机应用》2014年08期

【摘要】：微博的传播效果研究对于提高市场营销效率、加强舆情监控和准确发现热点具有重要作用。针对以前传播效果研究中未考虑用户个体差异的问题,提出一种基于行为分析的微博转发规模和传播深度预测方法。从微博用户自身、用户关系和微博内容3个方面提取9个相关特征,结合逻辑回归(LR)方法提出一种转发行为预测模型,并基于此模型结合信息沿用户传播特点,通过逐级对相邻用户迭代统计分析得到转发规模和传播深度预测方法。在新浪微博数据集上的实验结果表明,所提方法对转发规模和传播深度预测的正确率分别约为87.1%和81.6%,能较好地预测出信息传播效果。
[Abstract]:The research on the communication effect of Weibo plays an important role in improving the marketing efficiency, strengthening the monitoring of public opinion and accurately finding hot spots. Aiming at the problem that the user's individual differences were not taken into account in the previous research on propagation effect, a Weibo forwarding scale and propagation depth prediction method based on behavior analysis was proposed. From three aspects of Weibo user, user relationship and Weibo content, 9 related features are extracted, and a forwarding behavior prediction model is proposed combining with logical regression method. Based on this model, information is transmitted along the user. The prediction method of forwarding scale and propagation depth is obtained by iterative statistical analysis of adjacent users. The experimental results on Sina Weibo dataset show that the accuracy of the proposed method for the prediction of forwarding scale and propagation depth is about 87.1% and 81.6% respectively, which can well predict the effect of information dissemination.
【作者单位】：国家数字交换系统工程技术研究中心;
【基金】：国家863计划项目(2011AA010603,2011AA010605)
【分类号】：TP393.092

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