Twitter data laid almost bare: An insightful exploratory analyser

作者：

Highlights：

• Data mining methodology for spatio-temporal analysis of contents from social media.

• New proposed space-time-content based distance measure for cluster analysis.

• Deeper cluster characterization through association rule analysis.

• Implemented algorithms capable to computationally scale up to big datasets.

摘要

•Data mining methodology for spatio-temporal analysis of contents from social media.•New proposed space-time-content based distance measure for cluster analysis.•Deeper cluster characterization through association rule analysis.•Implemented algorithms capable to computationally scale up to big datasets.

论文关键词：Cluster analysis,Association rules,Text-spatio-temporal distance,Tweets,Social networks,Apache spark

论文评审过程：Received 10 April 2017, Revised 7 August 2017, Accepted 8 August 2017, Available online 22 August 2017, Version of Record 1 September 2017.

论文官网地址：https://doi.org/10.1016/j.eswa.2017.08.017