Mining Important Comments of Micro-Blog Based on Feature Weighting

Important comments of micro-blog not only reflect the views of users but also can influence the public’s opinion towards a particular topic. This paper presents a method of feature weighting based k-Nearest Neighbors for mining important comments of hot topics on Sina Weibo. By using feature weighting method, each selected feature is assigned to a corresponding weight. The comprehensive experimental results demonstrate that the presented method can better predict important comments than traditional k-Nearest Neighbors method. Furthermore, we show the presented method significantly outperforms the state-of-the-art classifiers.