Title : 
An Approach to Identify SPAM Tweets Based on Metadata
         
        
            Author : 
H?eusl;Johannes Forster;Daniel Kailer
         
        
            Author_Institution : 
Dept. of Comput. Sci. &
         
        
        
        
        
        
            Abstract : 
This paper introduces a concept for the classification of social media posts using twitter as an example. Thereby tweets are classified solely based on their metadata. We hereby use findings of network analysis and determine the strategic position, activity and reputation of a twitter user in order to classify his tweets into SPAM or HAM. Furthermore the next step of development for this concept, namely the determination of the entropy of a tweet, is described.
         
        
            Keywords : 
"Indexes","Twitter","Metadata","Media","Entropy","Business","Context"
         
        
        
            Conference_Titel : 
Web Intelligence and Intelligent Agent Technology (WI-IAT), 2015 IEEE / WIC / ACM International Conference on
         
        
        
            DOI : 
10.1109/WI-IAT.2015.44