CAJ | 학술논문

微博平台作为网络舆情传播渠道的典型代表，拥有强大的聚合民意、组织和分配资源能力，同时还有助长旅游突发事件的危机态势爆发的劣势。选取2010－2014年内发生的30个热点旅游突发事件作为研究对象，采用新浪微博API平台抓取微博数据，调用Matlab7畅1的SOM神经网络工具箱进行聚类，并采用指数函数方法进行拟合预测。研究结果表明，旅游突发事件的网络舆情传播态势主要分为六种类型，不同类型存在传播特征差异；对第六聚类旅游突发事件的微博传播态势的预测效果良好，与实际传播态势吻合。
미박평태작위망락여정전파거도적전형대표，옹유강대적취합민의、조직화분배자원능력，동시환유조장여유돌발사건적위궤태세폭발적열세。선취2010－2014년내발생적30개열점여유돌발사건작위연구대상，채용신랑미박API평태조취미박수거，조용Matlab7창1적SOM신경망락공구상진행취류，병채용지수함수방법진행의합예측。연구결과표명，여유돌발사건적망락여정전파태세주요분위륙충류형，불동류형존재전파특정차이；대제륙취류여유돌발사건적미박전파태세적예측효과량호，여실제전파태세문합。
First, We selected 30 hot tourism emergency events occurred from 2010 to 2014 as a the research ob-ject, write program to crawl microblog data on the microblog API platform and used SOM neural network toolbox in Matlab 7.1 to cluster microblog data.Second, we chose a result type and used the exponential function method for forecasting the spread trend.The result of the paper show that, microblog spread trend of tourism emergency events is mainly divided into six types, there are differences characteristics between different types; the predictive effect of microblog spread trend of sixth clustering result is good.