Title : 
Cues to Deception in Social Media Communications
         
        
            Author : 
Briscoe, Erica J. ; Appling, D. Scott ; Hayes, Heather
         
        
            Author_Institution : 
Georgia Tech Res. Inst., Atlanta, GA, USA
         
        
        
        
        
        
            Abstract : 
With the increasing reliance on social media as a dominant communication medium for current news and personal communications, communicators are capable of executing deception with relative ease. While past-related research has investigated written deception in traditional forms of computer mediated communication (e.g. email), we are interested determining if those same indicators hold in social media-like communication and if new, social-media specific linguistic cues to deception exist. Our contribution is two-fold: 1) we present results on human subjects experimentation to confirm existing and new linguistic cues to deception; 2) we present results on classifying deception from training machine learning classifiers using our best features to achieve an average 90% accuracy in cross fold validation.
         
        
            Keywords : 
learning (artificial intelligence); social networking (online); computer mediated communication; cross fold validation; current news; machine learning classifiers; personal communications; social media communications; written deception; Accuracy; Complexity theory; Electronic mail; Face; Media; Pragmatics; Social network services; computer mediated communication; deception; deception detection; deception generation; linguistic cues; online social networks;
         
        
        
        
            Conference_Titel : 
System Sciences (HICSS), 2014 47th Hawaii International Conference on
         
        
            Conference_Location : 
Waikoloa, HI
         
        
        
            DOI : 
10.1109/HICSS.2014.186