A framework for validating the merit of properties that predict the influence of a twitter user
作者：
Highlights：
• Classification algorithm separating between influential and non-influential users.
• Identification of properties that characterize influential users.
• Use of community structure to separate influential and non-influential users.
• Interactive annotation tool for labeling users and tweets regarding influence.
• Workflow for building a ground truth for influential users and tweets.
摘要
•Classification algorithm separating between influential and non-influential users.•Identification of properties that characterize influential users.•Use of community structure to separate influential and non-influential users.•Interactive annotation tool for labeling users and tweets regarding influence.•Workflow for building a ground truth for influential users and tweets.
论文关键词：Identification of influential users,Properties of influential users,Learning of influence,Community mining,Influential users in Twitter,Influential users,Influential tweets,Annotation of tweets,Mining,Twitter
论文评审过程：Available online 26 November 2014.
论文官网地址：https://doi.org/10.1016/j.eswa.2014.11.006
