Learning sequential features for cascade outbreak prediction

• Published in: Knowledge and information systems Vol. 57; no. 3; pp. 721 - 739
• Main Authors: Gou, Chengcheng, Shen, Huawei, Du, Pan, Wu, Dayong, Liu, Yue, Cheng, Xueqi
• Format: Journal Article
• Language: English
• Published: London Springer London 01.12.2018; Springer Nature B.V
• Subjects: Cascades; Computer Science; Data Mining and Knowledge Discovery; Database Management; Information Storage and Retrieval; Information systems; Information Systems and Communication Service; Information Systems Applications (incl.Internet); IT in Business; Neural networks; Outbreaks; Predictions; Recurrent neural networks; Short Paper; Social networks; Social network; Sequential feature; LSTM; Popularity prediction; Outbreak prediction

Information cascades are ubiquitous in various online social networks. Outbreak of cascades could cause huge and unexpected effects. Therefore, predicting the outbreak of cascades at early stage is of vital importance to avoid potential bad effects and take relevant actions. Existing methods either...