关键词: 事件检测, 事件摘要, 特征选取, 微博

Abstract: Microblog data have the characteristics of real-time dynamics, so we can monitor the microblog data to detect events in real life. However, the characteristics of the microblog data, such as the big data, short texts, rich social information and so on, also bring challenges. This paper proposes a novel event-detection algorithm based on microblog data—EDM algorithm, according to the textual characteristics of microblog data (retweeting, commenting, shorten url, hashtag and named entities), semantic features, time features and social information. Besides, this paper extracts keywords, named entities, the publishing time of posts and sentiment analysis for event summarization. Compared with LDA (latent Dirichlet allocation) model, the experimental results demonstrate that the proposed EDM algorithm works better in event detection and offers an intuitive event summary.

Key words: event detection, event summarization, feature selection, microblog