Wildlife Damage Estimation and Prediction Using Blog and Tweet Information

Wildlife damage estimation and prediction using blog and tweet information is conducted. Through a regressive analysis with the truth data about wildlife damage which is acquired by the federal and provincial governments and the blog and the tweet information about wildlife damage which are acquired in the same year, it is found that some possibility for estimation and prediction of wildlife damage. Through experiments, it is found that R value of the relations between the federal and provincial government gathered truth data of wildlife damages and the blog and the tweet information derived wildlife damages is more than 0.75. Also, it is possible to predict wildlife damage by using past truth data and the estimated wildlife damages. Therefore, it is concluded that the proposed method is applicable to estimate and predict wildlife damages. Keywords—Wildlife damage; Blog; Tweet; Big data analysis; Natural language recognition