Automated Linguistic Analysis Revealing Misrepresentation and Messaging (ALARMM)

The proposed Automated Linguistic Analysis Revealing Misrepresentation and Messaging (ALARMM) system significantly advances the state of the art in detecting deception in unstructured data such as Web sites and chat messages. Our research focuses on automated techniques based on linguistic theory that can detect both misrepresentations and hidden messages. The proposed work draws on the field of sociolinguistics for advanced statistical techniques capable of leveraging a wide range of morphological, lexical, and grammatical features. Formal representations from sociolinguistics are used to capture generalizations across types of deceptive language. We propose innovative experiments to provide a quantitative, metrics-based evaluation of the proof-of-concept ALARMM system.