Characterizing information propagation patterns in emergencies: A case study with Yiliang Earthquake

作者：

Highlights：

• We developed a Multinomial Naïve Bayes Classifier to categorize the microblog posts into five types according to the text content of posts.

• Different types of information had significantly different propagation patterns in terms of scale and topological features.

• Social media users exhibited significantly different interaction patterns for different types of information at different stages.

摘要

•We developed a Multinomial Naïve Bayes Classifier to categorize the microblog posts into five types according to the text content of posts.•Different types of information had significantly different propagation patterns in terms of scale and topological features.•Social media users exhibited significantly different interaction patterns for different types of information at different stages.

论文关键词：Social networks,Emergency management,Information propagation,Social media analytics

论文评审过程：Received 3 January 2017, Revised 29 August 2017, Accepted 30 August 2017, Available online 22 September 2017, Version of Record 22 September 2017.

论文官网地址：https://doi.org/10.1016/j.ijinfomgt.2017.08.008