DocumentCode :
264639
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
fYear :
2014
fDate :
6-9 Jan. 2014
Firstpage :
1435
Lastpage :
1443
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;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
System Sciences (HICSS), 2014 47th Hawaii International Conference on
Conference_Location :
Waikoloa, HI
Type :
conf
DOI :
10.1109/HICSS.2014.186
Filename :
6758783
Link To Document :
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