[目的/意义]微博在当前信息传播中起着重要作用，为有效预测微博热点及舆情导控，建立实时线性预警模型。[方法/过程]将采集的指标进行缺失值和异常值的处理后，对微博话题热度与大V影响力因子进行因子分析与逐步回归的比较，筛选出公共影响因子；再对其加权，探索不同权重调节因子下的最佳定量公式；用此公式每次输入当前时刻起前3小时的数据，预测当前时刻起后30分钟的加权值对应的话题词，每隔10分钟重新更新一遍参数。[结果/结论]实验证明该预测模型能大大降低数据采集解析和预测时间，保持较好的准确率，并可通过选择合适的阈值，进一步提升精确度。
[Purpose/significance] Microblog plays a significant role in information diffusion. Real-time linear model was set up in order to predict microblog hotspots and conduct public opinion effectively. [Method/process] Real-time linear model was used to predict the hot topic of microblog. Stepwise regression model was used to select impact factors affecting the hot topic of microblog. Missing value and outlier were processed. Comparison of microblog topics hotness and effectiveness factor of VIP was carried out according to factor analysis and stepwise regression. The common impact factors were filtered out and weighted. The appropriate formula was obtained by selecting different factors. The microblog data 3 hours before will be used before predicting microblog hot topic in 30 minutes. Parameters were updated every 10 minutes. [Result/conclusion] Experiments show that the prediction model could greatly reduce the time of data acquisition, analysis and prediction, maintain a relatively good accuracy. If a more appropriate threshold is selected, accuracy can be improved further.
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