基于改进人口模型的微博话题趋势预测

趋势预测问题是当前社会计算中的研究热点，但微博平台的话题趋势预测还处在探索阶段。在分析、抽取和定义事件趋势的影响因素的基础上，改进了人口模型使其适用于微博趋势预测，然后将改进的人口模型映射在神经网络上，并利用遗传优化的神经网络对事件的趋势进行预测。实验证明，该方法对于预测网络中长期酝酿的事件发展趋势效果明显，能够有效地预测事件的爆发点和发帖量，而且适用于小样本预测问题。

Based on improved malthusian model microblogging topic trend forecast

Although trend forecasting problem is the research focus of social computing, yet the topic trend forecast of micro logging platform is still at the exploratory stage. Based on the analyzing, extracting and defining the influencing factors of the trends of event, the improved Malthus model, which is more applicable to solve microblogging topic trend forecast problem is presented. Then the model is mapped to the neural network, and the genetic algorithms are used to predict the trend of events. Experiments show that this method can predict the trend of long-term events in the social network with good results, and can predict the outbreak point and posting volume effectively. It is worth nothing that the method is also suitable for small sample forecasting problems.