1. Linguistic Credibility Assessment

2. Emma – general comments on language Matt – tools for linguistic analysis Mary – case study

3. The Federalist Papers Series of 85 short essays – urged ratification of US Constitution Pseudonymously published, most were eventually claimed – Alexander Hamilton – James Madison – John Jay 12 remain of disputed authorship – Presumed to be by Madison or Hamilton

4. Automated Text Analysis Fung (2003) Classification problem, using SVM Used relative frequency of 70 most common words as features

5. 70 most common words

6. Classification Used machine learning to find 3 features to best separate Madison & Hamilton in documents with known author – to, upon, would Plot the 12 unknown documents along those 3 dimensions

7. Fung’s results: Disputed papers were by Madison

8. Language Complex system of communication unique to humanity – used for expressing thoughts – systematic – flexible allows for infinite combinations multiple ways to convey the same idea – not completely predictable

9. Patterns in Language & Language Use We make use of patterns in language for our purposes of communication – e.g. statement vs. question Mary sang at the concert. Did Mary sing at the concert? Mary sang at the concert? – e.g. Word order in conversation vs. poetry Soldiers brave were on the march. This information is used to classify types of language usage – e.g. genre, style, dialect, etc

10. Similarities & Differences What are factors that affect how language is used? – language in use (or dialect) – culture, social identity – situation purpose, topic domain, genre, social relationship between speakers, conversation type, etc – medium oral: in-person, by phone written: letter, chat, texts, financial documents – deceptive or truthful

11. From Theory to Cue Use theoretical predictions as basis for selecting cues to explore 5 domains – Arousal: e.g. expect quick rate of speech – Emotion: e.g. (for nervousness) expect more stuttering – Memory: e.g. expect fewer descriptive words – Cognition: e.g. expect less complex sentences – Communication: e.g. less likely to admit forgotten information

12. Manual Coding Systems Content-Based Criteria Analysis (CBCA) & Statement Validity Analysis (SVA) – Assumes statements derived from real memories will differ from invented ones in both content and quality – Score statements on the presence or absence of 19 criteria Reality Monitoring (RM) – Truthful memories are more likely to contain perceptual, contextual, & affective information Scientific Content Analysis (SCAN) – Used in criminal investigation statements

13. Some generalized linguistic cues (from DePaulo 2003) Less forthcoming than truth tellers Respond less (shorter responses, less elaboration), seem to hold back, speak at slower rate, longer response latency (less if planned) Tell stories that are less plausible More discrepancies, less engaging (more repetitions), behavior is less immediate (more indirect, fewer self-references), more uncertain, less fluent (more hesitations, errors, pauses), less active (gestures). Want story to be without error (fewer spontaneous corrections, less likely to admit can’t remember detail) Make a more negative impression Less cooperative, use more negative statements, words denoting anger & fear, offensive language, smile less, seem more defensive Are more tense Higher pitch, fidget more, pupils dilated for longer periods BUT! Remember cues are affected by context.

14. Research aims of CMI Discovering linguistic cues that are – reliable indicators of deception (or truthfulness) – context-independent as possible Note: Beware unrealistic claims of accuracy in detection – e.g. Cain’s Innocence “proved” through LVA – Consider the perspective & intentions: Researcher User’s understanding Business’ marketing Politician’s results-reporting – risk assessment vs. authoritative decision-making