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Stevens Lab
        
Text Analytics: Deception Detection and Gender Identification from Text
 

Deception is falsification of information. Detecting deception from text is a challenging problem. Deceptive text content, for example, may be found in social networking sites, emails scams, email phishing, blogs, chat rooms, etc. Our approach uses a combination of psychology, linguistics and statistical analysis to detect deception. Try it! We do not capture any personal information. The text your enter will be stored for further research.

Click the text files below to see examples of deceptive text content:

Example Description

FileName

Deceptive Cue

Too High?

Deceptive Example 1

employment.txt

article

too low

Deceptive Example 2

Gates.txt

you

too high

Deceptive Example 3

nigerian.txt

sixltr

too high

Deceptive Example 4

rental.txt

swear

too low

Deceptive Example 6

obama.txt

I

too low

Canada Tax Revenue Scam

letter.txt

othref

too high

Click on the link below to See Scam Examples From Craigslist:

Craigslist scam examples

 

Determine deceptiveness of text content By Entering Your Own Text,Uploading A File Or Entering the Website URL:

Enter Your Own Text To Detect Deceptive Content

Upload file to detect deceptive content

Determine Deceptiveness of Web URL

Where Am I?

 

Determine the Gender of An Existing File:

Determine gender of author of text (upload file)

Enter text to determine author's gender

 

 


Stevens Lab
        

Quick Links

Professor Rajarathnam Chandramouli

Professor K.P. (Suba) Subbalakshmi

Secure Systems Research

Electrical & Computer Engineering

School of Engineering & Science

Stevens Main Site

Contact  

Rajarathnam Chandramouli
Hattrick Chair Professor
315 Burchard Building
Phone: 201.216.8642
Fax:201.216.8246
rchandr1@stevens.edu

Stevens Lab