A Google Trends spatial clustering approach for a worldwide Twitter user geolocation
作者:
Highlights:
• We target the worldwide coordinate-level location of Twitter users
• We propose a novel Google Trends noun (GTN) spatial clustering approach
• GTN only uses historical tweets and public Web data (e.g., Google Trends)
• We collected a recent Twitter dataset with ground truth locations of 3,268 users
• The best overall results were achieved by the GTN DSCAN (GTN-DB) method
摘要
•We target the worldwide coordinate-level location of Twitter users•We propose a novel Google Trends noun (GTN) spatial clustering approach•GTN only uses historical tweets and public Web data (e.g., Google Trends)•We collected a recent Twitter dataset with ground truth locations of 3,268 users•The best overall results were achieved by the GTN DSCAN (GTN-DB) method
论文关键词:City-level geolocation,Clustering,Google Trends,Natural language processing,Twitter
论文评审过程:Received 15 January 2020, Revised 20 May 2020, Accepted 23 May 2020, Available online 12 June 2020, Version of Record 12 June 2020.
论文官网地址:https://doi.org/10.1016/j.ipm.2020.102312