Abstract: An apparatus and method for determining whether text is deceptive has a computer programmed with software that automatically analyzes text in digital form by at least one of statistical analysis of psycho-linguistic cues, IP geo-location, gender analysis, authorship analysis, and analysis to detect coded/camouflaged messages. The computer has truth data against which the text message can be compared and a graphical user interface. The computer may be connectable to the Internet and may obtain the text automatically. Speech-to-text software may be used to convert verbal messages to text for analysis. The system may be made available on a webpage, web service, on a computer or by a wireless device. The text may be emails, website content, tweets. In one embodiment, the system detects coded messages.

Abstract: A method and apparatus for automatically identifying harmful electronic messages, such as those presented in emails, on Craigslist or on Twitter, Facebook and other social media websites, features methodology for discriminating unwanted garbage communications (spam) and unwanted deceptive messages (scam) from wanted, truthful communications based upon patterns discernable from samples of each type of electronic communication. Methods are proposed that enable discrimination of wanted from unwanted communications in short electronic messages, such as on Twitter and for multilingual application.

Abstract: An apparatus and method for determining whether text is deceptive has a computer programmed with software that automatically analyzes text in digital form by at least one of statistical analysis of psycho-linguistic cues, IP geo-location, gender analysis, authorship analysis, and analysis to detect coded/camouflaged messages. The computer has truth data against which the text message can be compared and a graphical user interface. The computer may be connectable to the Internet and may obtain the text automatically. Speech-to-text software may be used to convert verbal messages to text for analysis. The system may be made available on a webpage, web service, on a computer or by a wireless device. The text may be emails, website content, tweets. In one embodiment, the system detects coded messages (FIG. 19).

Abstract: A method and apparatus for automatically identifying harmful electronic messages, such as those presented in emails, on Craigslist or on Twitter, Facebook and other social media websites, features methodology for discriminating unwanted garbage communications (spam) and unwanted deceptive messages (scam) from wanted, truthful communications based upon patterns discernable from samples of each type of electronic communication. Methods are proposed that enable discrimination of wanted from unwanted communications in short electronic messages, such as on Twitter and for multilingual application.