微博污染检测模型

信息传播的高速性加剧了谣言等网络污染在微博网络中的扩散。微博网络的用户量和信息量极为庞大。因此，对微博污染传播机制和污染检测手段的研究显得尤为重要。根据基于用户影响力建立的微博谣言传播模型，利用蚁群算法逆推污染传播路径，搜索受染用户，并分别以Twitter和新浪微博为实验平台，通过对比分析验证了模型的可行性。实验结果表明：模型通过对受染个体的搜索，缩小了污染的检测范围，提高了微博污染的治理效率和准确性。

Pollution detection model in microblogging

The high speed of the information propagation exacerbates the diffusion of rumors or other network pollutions in the microblogging. As the size of microbloggers and information of sub-networks in microblogging is enormous, the study of the propagation mechanism of microblogging pollution and pollution detection becomes very significant. According to the rumor spreading model for the microblogging established on the basis of influence of users, in this paper, ant colony algorithm was used to search for the rumor spreading route. Based on the data obtained from Twitter and Sina microblogging, the feasibility of the model was verified by comparison and analysis. The results show that: with the search of the affected individual, this model narrows down the pollution detection range, and improves the efficiency and accuracy of pollution management in microblogging.