situational and psychological factors predicting deception and its detection:

Situational and Psychological FactorsPredicting Deception and its Detection:

Implications for Non-Cognitive Assessment

Jeff Hancock

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?

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

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

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

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

1. Deception production

How frequently does lying occur?

1. Deception production

How frequently does lying occur?

• retrospective identification• message-by-message identification• diary studies• ground truth based

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 exchangeRange from 0 lies to 14 liesSelf-presentation goal (‘likeable’) increases deception

1. Deception production

How frequently does lying occur?

• retrospective identification• message-by-message identification• diary studies• ground truth based

• type message• rate deceptiveness of message• message and rating is sent to our corpus

Lie-M

• type message• rate deceptiveness of message• message and rating is sent to our corpus

Lie-M

6% of all messageswere deceptive

1. Deception production

How frequently does lying occur?

• retrospective identification• message-by-message identification• diary studies• ground truth based

How do different media affect lying and honesty?

1. basic facts, examples, principles

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

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

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

nonverbalphysiologicalverbal

1. basic facts, examples, principles

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

nonverbalphysiologicalverbal

1. basic facts, examples, principles

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

nonverbalphysiologicalverbal

DePaulo et al (2003) meta-analysis

• more tense• higher vocal pitch• fidgeting

1. basic facts, examples, principles

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

nonverbalphysiologicalverbal

DePaulo et al (2003) meta-analysis

• more tense• higher vocal pitch• fidgeting

eye gaze: unreliable

1. basic facts, examples, principles

0

5

10

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45

SocialDistanceTheory

HIGH

LOW

FtF Phone EmailInstant

Message

Frequencyof Lies perInteraction

How do different media affect lying and honesty?

0

5

10

15

20

25

30

35

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45

SocialDistanceTheory

HIGH

LOW

FtF Phone EmailInstant

Message

Nonverbal prediction

Frequencyof Lies perInteraction

0

5

10

15

20

25

30

35

40

45

SocialDistanceTheory

HIGH

LOW

FtF Phone EmailInstant

Message

Social Distance Theory

< < <

(DePaulo et al, 1996)

Social Distance

Frequencyof Lies perInteraction

Nonverbal prediction

0

5

10

15

20

25

30

35

40

45

SocialDistanceTheory

HIGH

LOW

FtF Phone EmailInstant

Message

Social Distance Theory(DePaulo et al, 1996)

Frequencyof Lies perInteraction Media Richness Theory

(Daft & Lengel, 1984; 1986)

Nonverbal prediction

0

5

10

15

20

25

30

35

40

45

SocialDistanceTheory

HIGH

LOW

FtF Phone EmailInstant

Message

Social Distance Theory

Media Richness Theory

Richness > > >

(Daft & Lengel, 1984; 1986)

Frequencyof Lies perInteraction

Nonverbal prediction

0

5

10

15

20

25

30

35

40

45

Line 1

SocialDistanceTheory

HIGH

LOW

FtF Phone EmailInstant

Message

Social Distance Theory

Media Richness Theory

Richness > > >

(Daft & Lengel, 1984; 1986)

Frequencyof Lies perInteraction

Nonverbal prediction

0

5

10

15

20

25

30

35

40

45

Line 1

SocialDistanceTheory

HIGH

LOW

Frequencyof Lies perInteraction

FtF Phone EmailInstant

Message

Social Distance Theory

Social Distance

Media Richness Theory

Richness

FtF Phone IM Email

Media Features

Synchronous X X n

Recordless X X n

Distributed X X X

Lying predictions

Feature-based 2 1 2 3

Media Richness 1 2 3 4

Social Distance 4 3 2 1

Feature Based Approach

PDA-based journal

0

10

20

30

40

50

60

70

Line 1

SocialDistanceTheory

Social Distance Theory

Media Richness Theory

% of Lies per Interaction

Nonverbal prediction

0

10

20

30

40

50

60

70

Line 1

SocialDistanceTheory

Line 3

Social Distance Theory

Media Richness Theory

% of Lies per Interaction

27%

37%

21%

14%Data

FtF Phone EmailInstant

Message

Nonverbal prediction

10

15

20

25

30

35

40

Line 1

Line 2

Line 3

DistributedSimultaneityRecordless

***

** n* * n

% of Lies per Interaction

FtF Phone EmailInstantMessage

27%

37%

21%

14%

Features Model

10

15

20

25

30

35

40

Line 1

Line 2

Line 3

DistributedSimultaneityRecordless

***

** n* * n

% of Lies per Interaction

FtF Phone EmailInstantMessage

27%

37%

21%

14%

Features Model

• 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

Visual Anonymity

Private Self-Awareness

Public Self-Awareness

Self-Disclosure

self-disclosure and honesty in mediated contexts

Joinson (2001)

1. Deception production

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

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

NOTMONOTLITHIC

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

NOTMONOTLITHIC

GOALTENSIONS

Female Male

Female Male

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

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

2. Detecting deception

acoustic profiles•Judee Burgoon’s group• pitch profile changes• large effects for energy and f0 features

2. Detecting deception

New, computer-assisted methods

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

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 1st person, more 3rd person references• fewer exclusive words• more negative emotion terms• changes in detail level

2. Detecting deception

New, computer-assisted methods

Sender Receiver

“to not tell the truth,the whole truth, and nothing but the truth”on two topics.

Discuss 4 topics

“Maintain the conversation”

Sender Receiver

“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

100

110

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160

170

Sender Receiver

Deception

Truth

Word Count

100

110

120

130

140

150

160

170

Sender Receiver

Deception

Truth

Word Count

28% increase

0

1

2

3

4

5

6

7

8

9

Sender Receiver

deceptiontruth

%words

1st person singular

0

1

2

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9

Sender Receiver

deceptiontruth

%words

1st person singular

0

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9

Sender Receiver Sender Receiver

%words

deceptiontruth

2nd person1st person singular

0

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9

Sender Receiver Sender Receiver Sender Receiver

2nd person 3rd person

%words

deceptiontruth

1st person singular

0

1

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5

6

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8

9

Sender Receiver Sender Receiver Sender Receiver

1st person singular 2nd person 3rd person

%words

deceptiontruth

Fewer 1st person singularMore 3rd person

Psychological effect Language process NLP approach/tool

Distancing the speaker from the lie

Non-immediate language - reduced 1st 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 clausesChanges in evidentiality - subjective vs. factual presentation- changes in reporting verbs (e.g., saw, hear)

Syntactic parserSentence-level subjective/objective classifier; Reporting verb analyzer

Increased cognitive load Reduced coherenceReduced use of exclusive terms (e.g., never)

CohmetrixLIWC

Collaborative processes Linguistic style matchingQuestion – answer patternsSequential discourse analysis

Auto-correlationSequence prediction

Keila & Skillicorn (2005)

Keila & Skillicorn (2005)

More deceptive

• 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.

• 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

• 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)

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

Situational and Psychological FactorsPredicting Deception and its Detection:

Implications for Non-Cognitive Assessment

Jeff Hancock