An investigation of data and text mining methods for real world deception detection

Expert Systems with Applications

Volumn 38, Issue 7, 2011, Pages 8392-8398

  Fuller, Christie M ^a   Biros, David P ^b   Delen, Dursun ^b  

^a LOUISIANA TECH UNIVERSITY   (United States)

^b OKLAHOMA STATE UNIVERSITY   (United States)

Author keywords

Classification; Credibility assessment; Data mining; Deception detection; Information fusion; Text mining

Indexed keywords

ACCURACY RATE; ARTIFICIAL NEURAL NETWORK; CLASSIFICATION; CLASSIFICATION ACCURACY; CLASSIFICATION MODELS; CREDIBILITY ASSESSMENT; CROSS VALIDATION; DECEPTION DETECTION; REAL WORLD DATA; RESEARCH STUDIES; SECURITY PERSONNEL; TEXT MINING;

DECISION TREES; INFORMATION FUSION; NEURAL NETWORKS; TEXT PROCESSING;

DATA MINING;

EID: 79952437990     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2011.01.032     Document Type: Article

References (29)

1. Adkins, M., Twitchell, D., Burgoon, J. K., Nunamaker Jr, J. F. (2004). Advances in automated deception detection in text-based computer-mediated communication. In: Paper presented at the enabling technologies for simulation science VIII, Orlando, FL, USA.
2. Battelle Memorial Institute (2007). Efficacy of prototype credibility assessment technologies: PCASS final report.
3. M.J.A. Berry, and G.S. Linoff Data mining techniques 2nd ed. 2004 Wiley Publishing Indianapolis, Indiana
4. C.F. Bond, and B.M. DePaulo Accuracy of deception judgments Personality and Social Psychology Reports 10 3 2006 214 234
5. G.D. Bond, and A.Y. Lee Language of lies in prison: Linguistic classification of prisoners' truthful and deceptive natural language Applied Cognitive Psychology 19 3 2005 313
6. L. Breiman, J.H. Friedman, R.A. Olshen, and C.J. Stone Classification and regression trees 1984 Wadsworth & Brooks Books & Software Monterey, CA
7. D.B. Buller, and J.K. Burgoon Interpersonal deception theory Communication Theory 6 3 1996 203 242
8. H. Cunningham Gate, a general architecture for text engineering Computers and the Humanities 36 2 2002 223 254 (Pubitemid 44947904)
9. B.M. DePaulo, J.J. Lindsay, B.E. Malone, L. Muhlenbruck, K. Charlton, and H. Cooper Cues to deception Psychological Bulletin 129 1 2003 74 118 (Pubitemid 41103269)
10. R. Feldman, and J. Sanger The text mining handbook: Advanced approaches in analyzing unstructured data 2007 Cambridge University Press New York
11. M.G. Frank, and T.H. Feeley To catch a liar: Challenges for research in lie detection training Journal of Applied Communication Research 31 1 2003 58 75 (Pubitemid 36256533)
12. George, J. F., Keane, B. T. (2006). Deception detection by third party observers. In: Paper presented at the deception detection symposium, 39th annual Hawaii international conference on system sciences.
13. Hancock, J., Thom-Santelli, J., Ritchie, T. (2004). Deception and design: The impact of communication technology on lying behavior. In: Paper presented at the SIGCHI conference on Human factors in computing systems, Vienna, Austria, April 24-29.
14. Hancock, J. T., Curry, L., Goorha, S., Woodworth, M. (2005). Automated linguistic analysis of deceptive and truthful synchronous computer-mediated communication. In: Paper presented at the 38th annual Hawaii international conference on system sciences.
15. Harris, J. C., McQuarrie, A. D. (2009). The preliminary credibility assessment system embedded algorithm description and validation results. Johns Hopkins University Applied Physics Laboratory Report Number GED-R-06-7571.
16. S. Haykin Neural networks and learning machines 3rd ed. 2008 Prentice Hall New Jersey
17. Indictment puts internet pranksters on notice (2008). An article on CNN Website. Accessed 16.5.08.
18. M.K. Johnson, and C.L. Raye Reality monitoring Psychological Review 88 1 1981 67 85
19. G. Kohnken Speech and deception of eyewitnesses: An information processing approach F.L. Denmark, Social/ecological psychology and the psychology of women 1985 Elsevier Science Publishers North-Holland
20. S.A. McCornack Information manipulation theory Communication Monographs 59 1 1992 1 16
21. National Research Council (2003). The polygraph and lie detection. Technical report, Washington, DC.
22. J.W. Pennebaker, and M.E. Francis Linguistic inquiry and word count: Liwc 2001 2001 Erlbaum Publishers Mahwah, NJ
23. D.A. Pollina, A.B. Dollins, S.M. Senter, D.J. Krapohl, and A.H. Ryan Comparison of polygraph data obtained from individuals involved in mock crimes and actual criminal investigations Journal of Applied Psychology 89 6 2004 1099 1105 (Pubitemid 40019511)
24. S.M. Senter, J. Waller, and D.J. Krapohl Validation studies for the preliminary credibility assessment screening system (pcass) 2006 Department of Defense Polygraph Institute
25. Twitchell, D., Jensen, M. L., Burgoon, J. K., Nunamaker Jr., J. F., (2004). Detecting deception in secondary screening interviews using linguistic analysis. In: Paper presented at the 7th international IEEE conference on intelligent transportation systems.
26. Twitchell, D. P., Biros, D. P., Adkins, M., Forsgren, N., Burgoon, J. K., Nunamaker Jr, J. F. (2006). Automated determination of the veracity of interview statements from people of interest to an operational security force. In: Paper presented at the 39th annual Hawaii international conference on system sciences.
27. A. Vrij Detecting lies and deceit: The psychology of lying and the implications for professional practice 2000 John Wiley & Sons New York
28. L. Zhou, J.K. Burgoon, J. Nunamaker, F. Jay, and D.P. Twitchell Automated linguistics based cues for detecting deception in text-based asynchronous computer-mediated communication: An empirical investigation Group Decision and Negotiation 13 1 2004 81 106 (Pubitemid 39046078)
29. L. Zhou, J.K. Burgoon, D.P. Twitchell, T.T. Qin, and J.F. Nunamaker A comparison of classification methods for predicting deception in computer-mediated communication Journal of Management Information Systems 20 4 2004 139 165