Presentation is loading. Please wait.

Presentation is loading. Please wait.

Situational and Psychological Factors Predicting Deception and its Detection: Implications for Non-Cognitive Assessment Jeff Hancock.

Similar presentations


Presentation on theme: "Situational and Psychological Factors Predicting Deception and its Detection: Implications for Non-Cognitive Assessment Jeff Hancock."— Presentation transcript:

1 Situational and Psychological Factors Predicting Deception and its Detection: Implications for Non-Cognitive Assessment Jeff Hancock

2 Some questions about faking 1.Can people fake when instructed? 2.What is prevalence of faking? 3.What is the nature of faking? 4.Can faking be prevented or reduced? 5.Can faking be detected? 6.Can people avoid detection?

3 Some questions about faking 1.Can people fake when instructed? 2.What is prevalence of faking? 3.What is the nature of faking? 4.Can faking be prevented or reduced? 5.Can faking be detected? 6.Can people avoid detection? Deception Research production

4 Some questions about faking 1.Can people fake when instructed? 2.What is prevalence of faking? 3.What is the nature of faking? 4.Can faking be prevented or reduced? 5.Can faking be detected? 6.Can people avoid detection? Deception Research production motivations

5 Some questions about faking 1.Can people fake when instructed? 2.What is prevalence of faking? 3.What is the nature of faking? 4.Can faking be prevented or reduced? 5.Can faking be detected? 6.Can people avoid detection? Deception Research production motivations detection

6 any intentional control of information in a message to create a false belief in the receiver of the message Deception Defined 1. Deception production a successful or unsuccessful deliberate attempt, without forewarning, to create in another a belief which the communicator considers to be untrue --Burgoon --Vrij

7 1. Deception production How frequently does lying occur?

8 1. Deception production How frequently does lying occur? retrospective identification message-by-message identification diary studies ground truth based

9 1. Deception production How frequently does lying occur? retrospective identification message-by-message identification diary studies ground truth based 1.75 lies identified in a 10 minute exchange Range from 0 lies to 14 lies Self-presentation goal (‘likeable’) increases deception

10 1. Deception production How frequently does lying occur? retrospective identification message-by-message identification diary studies ground truth based

11 type message rate deceptiveness of message message and rating is sent to our corpus Lie-M

12 type message rate deceptiveness of message message and rating is sent to our corpus Lie-M 6% of all messages were deceptive

13 1. Deception production How frequently does lying occur? retrospective identification message-by-message identification diary studies ground truth based

14 How do different media affect lying and honesty? 1. basic facts, examples, principles

15 How do different media affect lying and honesty? “Electronic mail is a godsend. With e-mail we needn’t worry about so much as a quiver in our voice or a tremor in our pinkie when telling a lie. Email is a first rate deception- enabler.” ~Keyes (2004) The Post-Truth Era 1. basic facts, examples, principles

16 How do different media affect lying and honesty? “Electronic mail is a godsend. With e-mail we needn’t worry about so much as a quiver in our voice or a tremor in our pinkie when telling a lie. Email is a first rate deception- enabler.” ~Keyes (2004) The Post-Truth Era 1. basic facts, examples, principles

17 How do different media affect lying and honesty? “Electronic mail is a godsend. With e-mail we needn’t worry about so much as a quiver in our voice or a tremor in our pinkie when telling a lie. Email is a first rate deception- enabler.” ~Keyes (2004) The Post-Truth Era Three ways to catch a liar nonverbal physiological verbal 1. basic facts, examples, principles

18 How do different media affect lying and honesty? “Electronic mail is a godsend. With e-mail we needn’t worry about so much as a quiver in our voice or a tremor in our pinkie when telling a lie. Email is a first rate deception- enabler.” ~Keyes (2004) The Post-Truth Era Three ways to catch a liar nonverbal physiological verbal 1. basic facts, examples, principles

19 How do different media affect lying and honesty? “Electronic mail is a godsend. With e-mail we needn’t worry about so much as a quiver in our voice or a tremor in our pinkie when telling a lie. Email is a first rate deception- enabler.” ~Keyes (2004) The Post-Truth Era Three ways to catch a liar nonverbal physiological verbal DePaulo et al (2003) meta-analysis more tense higher vocal pitch fidgeting 1. basic facts, examples, principles

20 How do different media affect lying and honesty? “Electronic mail is a godsend. With e-mail we needn’t worry about so much as a quiver in our voice or a tremor in our pinkie when telling a lie. Email is a first rate deception- enabler.” ~Keyes (2004) The Post-Truth Era Three ways to catch a liar nonverbal physiological verbal DePaulo et al (2003) meta-analysis more tense higher vocal pitch fidgeting eye gaze: unreliable 1. basic facts, examples, principles

21 HIGH LOW FtFPhoneEmail Instant Message Frequency of Lies per Interaction How do different media affect lying and honesty?

22 HIGH LOW FtFPhoneEmail Instant Message Nonverbal prediction Frequency of Lies per Interaction

23 HIGH LOW FtFPhoneEmail Instant Message Social Distance Theory <<< (DePaulo et al, 1996) Social Distance Frequency of Lies per Interaction Nonverbal prediction

24 HIGH LOW FtFPhoneEmail Instant Message Social Distance Theory (DePaulo et al, 1996) Frequency of Lies per Interaction Media Richness Theory (Daft & Lengel, 1984; 1986) Nonverbal prediction

25 HIGH LOW FtFPhoneEmail Instant Message Social Distance Theory Media Richness Theory Richness >>> (Daft & Lengel, 1984; 1986) Frequency of Lies per Interaction Nonverbal prediction

26 HIGH LOW FtFPhoneEmail Instant Message Social Distance Theory Media Richness Theory Richness >>> (Daft & Lengel, 1984; 1986) Frequency of Lies per Interaction Nonverbal prediction

27 HIGH LOW Frequency of Lies per Interaction FtFPhoneEmail Instant Message Social Distance Theory Social Distance Media Richness Theory Richness

28 FtFPhoneIMEmail Media Features SynchronousXX n RecordlessXX n DistributedXXX Lying predictions Feature-based2123 Media Richness1234 Social Distance4321 Feature Based Approach

29 PDA-based journal

30 Social Distance Theory Media Richness Theory % of Lies per Interaction Nonverbal prediction

31 Social Distance Theory Media Richness Theory % of Lies per Interaction 27% 37% 21% 14% Data FtFPhoneEmail Instant Message Nonverbal prediction

32 Distributed Simultaneity Recordless *** ** n ** n % of Lies per Interaction FtFPhoneEmail Instant Message 27% 37% 21% 14% Features Model

33 Distributed Simultaneity Recordless *** ** n ** n % of Lies per Interaction FtFPhoneEmail Instant Message 27% 37% 21% 14% Features Model

34 more symptoms & undesirable behaviors reported (Griest, Klein & VanCura, 1973) more sexual partners and symptoms reported (Robinson & West, 1992) more honest, candid answers in pre-clinical psychiatric interviews (Ferriter, 1993) 20% of telephone callers vs. 50% of email contacts report suicidal feelings (The Scotsman, 1999) when interviewed by computer compared to face-to-face: High levels of self-disclosure and honesty in text-based contexts 1. Deception production

35 Visual Anonymity Private Self-Awareness Public Self-Awareness Self-Disclosure self-disclosure and honesty in mediated contexts Joinson (2001) 1. Deception production

36 How frequently does lying occur? retrospective identification message-by-message identification diary studies ground truth based Why do people lie? - Situational factors - Self-presentation goals

37 1. Deception production How frequently does lying occur? retrospective identification message-by-message identification diary studies ground truth based Why do people lie? - Situational factors - Self-presentation goals NOT MONOTLITHIC

38 1. Deception production How frequently does lying occur? retrospective identification message-by-message identification diary studies ground truth based Why do people lie? - Situational factors - Self-presentation goals NOT MONOTLITHIC GOAL TENSIONS

39

40 Female Male

41

42 Some questions about faking 1.Can people fake when instructed? 2.What is prevalence of faking? 3.What is the nature of faking? 4.Can faking be prevented or reduced? 5.Can faking be detected? 6.Can people avoid detection? Deception Research production motivations - self-presentation goals fundamental - self-presentation goals are tension-based - self-presentation goals can be primed

43 Some questions about faking 1.Can people fake when instructed? 2.What is prevalence of faking? 3.What is the nature of faking? 4.Can faking be prevented or reduced? 5.Can faking be detected? 6.Can people avoid detection? Deception Research production motivations detection

44 2. Detecting deception

45 acoustic profiles Judee Burgoon’s group pitch profile changes large effects for energy and f0 features 2. Detecting deception New, computer-assisted methods

46 acoustic profiles Judee Burgoon’s group pitch profile changes large effects for energy and f0 features facial features micro-facial expressions (FACS), Mark Frank 2. Detecting deception New, computer-assisted methods

47 acoustic profiles Judee Burgoon’s group pitch profile changes large effects for energy and f0 features facial features micro-facial expressions (FACS), Mark Frank linguistic footprints – text-based fewer 1 st person, more 3 rd person references fewer exclusive words more negative emotion terms changes in detail level 2. Detecting deception New, computer-assisted methods

48 SenderReceiver “to not tell the truth, the whole truth, and nothing but the truth” on two topics. Discuss 4 topics “Maintain the conversation”

49 SenderReceiver “to not tell the truth, the whole truth, and nothing but the truth” on two topics. Discuss 4 topics “Maintain the conversation” transcripts were analyzed with Pennebaker’s Linguistic Inquiry and Word Count (LIWC) program LIWC analyzes transcripts on a word-by-word basis and compares words against a dictionary of words divided into 74 psychologically relevant linguistic dimensions

50 Word Count

51 28% increase

52 deception truth % words 1 st person singular

53 deception truth % words 1 st person singular

54 % words deception truth 2 nd person 1 st person singular

55 2 nd person3 rd person % words deception truth 1 st person singular

56 2 nd person3 rd person % words deception truth Fewer 1 st person singular More 3 rd person

57 Psychological effectLanguage processNLP approach/tool Distancing the speaker from the lie Non-immediate language - reduced 1 st person singular - increased use of passive voice - reduced transitivity - semantic roles (agent v. patient) Syntactic parser and semantic role identifier Increased levels of negative affect Changes in affect terms - increased negative affect valence - attitude type - contextual disambiguation Sentence- and phrase- level sentiment analysis Attempt to convey a convincing story Changes in detail level - noun phrase complexity - dependent/relative clauses Changes in evidentiality - subjective vs. factual presentation - changes in reporting verbs (e.g., saw, hear) Syntactic parser Sentence-level subjective/objective classifier; Reporting verb analyzer Increased cognitive loadReduced coherence Reduced use of exclusive terms (e.g., never) Cohmetrix LIWC Collaborative processesLinguistic style matching Question – answer patterns Sequential discourse analysis Auto-correlation Sequence prediction

58 Keila & Skillicorn (2005)

59 More deceptive

60 105 subjects generating two email texts each Each completed the Eysenck Personality Questionnaire: –Extraversion: outgoing - shy –Neuroticism: worrying - relaxed –Psychoticism: toughminded - sympathetic –Lie Scale - measures social desirabity Each then composed two emails: –“To a good friend whom they hadn’t seen for quite some time” –One concerned past activities over the previous week –The other concerned planned activities over the next week. Each message took around 10 minutes to compose and submit by HTML form. The resulting 210 texts contain 65,000 words.

61 Texts split by level of Social Desirability –measured by EPQ-R Lie Scale –Split scores by greater +/- 1 Std Dev of mean Resulted in two groups –High SDR Authors (N=21) –Low SDR Authors (N=22) Corpus comparison of these two groups using Wmatrix software (Rayson 2003, 2005; cf. Oberlander & Gill, 2006) –Identified features significantly over-used or under- used by each group (using log-likelihood) –All features reported p<0.001

62 Hi SDR scorers over-used: –You –‘Personal names’ (Richard, Kathy, London) –words related to ‘Business: Selling’ (shopping, buy, sales, bought) Low SDR scorers over-used: –‘Mental object: Means, method’ words (way, system, method, tactical, pattern, set-up)

63 Some questions about faking 1.Can people fake when instructed? 2.What is prevalence of faking? 3.What is the nature of faking? 4.Can faking be prevented or reduced? 5.Can faking be detected? 6.Can people avoid detection? Deception Research production motivations detection

64 Situational and Psychological Factors Predicting Deception and its Detection: Implications for Non-Cognitive Assessment Jeff Hancock


Download ppt "Situational and Psychological Factors Predicting Deception and its Detection: Implications for Non-Cognitive Assessment Jeff Hancock."

Similar presentations


Ads by Google