Abstract
Microblogging is an important source of information about what is happening in the real world. In this work, we propose a novel approach for real-time event detection targeting accident and disaster events (ADEs) using microblogs from Sina Weibo. Our aim is to detect out every microblog which reports a real-world occurrence of a target event from the microblog stream. We formulate the event detection problem as a classification problem using microblog-based features, linguistic features, content features, and event features. We propose a street-level location extraction method based on the textual content to cooperate geo-information extraction. In order to deliver fresh events, we use a temporal analysis method to filter away past events. We compare our method with two state-of-the-art baselines on event detection, and achieve improvements in both precision and recall.
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Feng, X., Zhang, S., Liang, W., Tu, Z. (2014). Real-Time Event Detection Based on Geo Extraction and Temporal Analysis. In: Luo, X., Yu, J.X., Li, Z. (eds) Advanced Data Mining and Applications. ADMA 2014. Lecture Notes in Computer Science(), vol 8933. Springer, Cham. https://doi.org/10.1007/978-3-319-14717-8_11
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DOI: https://doi.org/10.1007/978-3-319-14717-8_11
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