Transcript Situational and Psychological Factors Predicting Deception

Situational and Psychological Factors
Predicting Deception and its Detection:
Implications for Non-Cognitive Assessment
Jeff Hancock
Some questions about faking
1.
2.
3.
4.
5.
6.
Can people fake when instructed?
What is prevalence of faking?
What is the nature of faking?
Can faking be prevented or reduced?
Can faking be detected?
Can people avoid detection?
Some questions about faking
Deception Research
1.
2.
3.
4.
5.
6.
Can people fake when instructed?
What is prevalence of faking?
What is the nature of faking?
Can faking be prevented or reduced?
Can faking be detected?
Can people avoid detection?
production
Some questions about faking
Deception Research
1.
2.
3.
4.
5.
6.
Can people fake when instructed?
What is prevalence of faking?
What is the nature of faking?
Can faking be prevented or reduced?
Can faking be detected?
Can people avoid detection?
production
motivations
Some questions about faking
Deception Research
1.
2.
3.
4.
5.
6.
Can people fake when instructed?
What is prevalence of faking?
What is the nature of faking?
Can faking be prevented or reduced?
Can faking be detected?
Can people avoid detection?
production
motivations
detection
1. Deception production
Deception Defined
any intentional control of information in a
message to create a false belief in the receiver
of the message
--Burgoon
a successful or unsuccessful deliberate attempt,
without forewarning, to create in another a belief
which the communicator considers to be untrue
--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 exchange
Range from 0 lies to 14 lies
Self-presentation goal (‘likeable’) increases deception
1. Deception production
How frequently does lying occur?
• retrospective identification
• message-by-message identification
• diary studies
• ground truth based
Lie-M
• 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
6% of all messages
were deceptive
1. Deception production
How frequently does lying occur?
• retrospective identification
• message-by-message identification
• diary studies
• ground truth based
1. basic facts, examples, principles
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 deceptionenabler.”
~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 deceptionenabler.”
~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 deceptionenabler.”
~Keyes (2004) The Post-Truth Era
Three ways to catch a liar
nonverbal
physiological
verbal
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 deceptionenabler.”
~Keyes (2004) The Post-Truth Era
Three ways to catch a liar
nonverbal
physiological
verbal
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 deceptionenabler.”
~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
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 deceptionenabler.”
~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
How do different media affect lying and honesty?
45
HIGH
40
35
30
Frequency
25
of Lies per
Interaction
Social
Distance
Theory
20
15
10
5
LOW
0
FtF
Phone
Instant
Message
Email
Nonverbal prediction
45
HIGH
40
35
30
Frequency
25
of Lies per
Interaction
Social
Distance
Theory
20
15
10
5
LOW
0
FtF
Phone
Instant
Message
Email
Nonverbal prediction
45
HIGH
40
Social Distance Theory
(DePaulo et al, 1996)
35
30
Frequency
25
of Lies per
Interaction
Social
Distance
Theory
20
15
10
5
LOW
0
FtF
<
Phone
<
Instant
Message
< Email
Social Distance
Nonverbal prediction
45
HIGH
40
Social Distance Theory
(DePaulo et al, 1996)
35
30
Frequency
25
of Lies per
Interaction
Social
Distance
Media
Richness Theory
Theory
(Daft & Lengel, 1984; 1986)
20
15
10
5
LOW
0
FtF
Phone
Instant
Message
Email
Nonverbal prediction
45
HIGH
40
Social Distance Theory
35
30
Frequency
25
of Lies per
Interaction
Social
Distance
Media
Richness Theory
Theory
(Daft & Lengel, 1984; 1986)
20
15
10
5
LOW
0
Richness
FtF
>
Phone
Instant
Message
>
> Email
Nonverbal prediction
45
HIGH
40
Social Distance Theory
35
Line 1
30
Frequency
25
of Lies per
Interaction
Media Richness Theory
Social
(Daft & Lengel, 1984; 1986)
Distance
Theory
20
15
10
5
LOW
0
Richness
FtF
>
Phone
Instant
Message
>
> Email
45
HIGH
40
Social Distance Theory
35
Line 1
30
Frequency
25
of Lies per
Interaction
Media Richness Theory
Social
Distance
Theory
20
15
10
5
LOW
0
Richness
FtF
Phone
Instant
Message
Email
Social Distance
Feature Based Approach
FtF
Phone
IM
Email
Synchronous
X
X
n
Recordless
X
X
n
X
X
X
Media Features
Distributed
Lying predictions
Feature-based
2
1
2
3
Media Richness
1
2
3
4
Social Distance
4
3
2
1
PDA-based journal
% of Lies
per Interaction
70
Nonverbal prediction
60
Social Distance Theory
50
Line 1
40
30
20
10
0
Social
Media
Richness Theory
Distance
Theory
% of Lies
per Interaction
70
Nonverbal prediction
60
Social
Distance
Theory
Line
1
50
Social
Distance
Media
Richness Theory
Theory
Line 3
40
37%
30
20
27%
21%
10
14%
0
FtF
Phone
Instant
Message
Email
Data
% of Lies
per Interaction
40
35
37%
30
25
Line 1
Line 2
Line 3
27%
20
21%
15
14%
10
FtF
Phone
Instant
Message
Email
Features Model
*
*
*
*
*
*n
*
Distributed
Simultaneity
Recordless
n
% of Lies
per Interaction
40
35
37%
30
25
Line 1
Line 2
Line 3
27%
20
21%
15
14%
10
FtF
Phone
*
*
*
*
*
Instant
Message
*n
n
Email
Features Model
*
Distributed
Simultaneity
Recordless
1. Deception production
High levels of self-disclosure and honesty in text-based contexts
when interviewed by computer compared to face-to-face:
• 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)
1. Deception production
self-disclosure and honesty in mediated contexts
Joinson (2001)
Private Self-Awareness
Self-Disclosure
Visual Anonymity
Public Self-Awareness
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
NOT
MONOTLITHIC
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
Female
Male
Female
Male
Some questions about faking
Deception Research
1.
2.
3.
4.
5.
6.
Can people fake when instructed?
What is prevalence of faking?
What is the nature of faking?
Can faking be prevented or reduced?
Can faking be detected?
Can people avoid detection?
production
motivations
- self-presentation goals fundamental
- self-presentation goals are tension-based
- self-presentation goals can be primed
Some questions about faking
Deception Research
1.
2.
3.
4.
5.
6.
Can people fake when instructed?
What is prevalence of faking?
What is the nature of faking?
Can faking be prevented or reduced?
Can faking be detected?
Can people avoid detection?
production
motivations
detection
2. Detecting deception
2. Detecting deception
New, computer-assisted methods
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
“to not tell the
truth,
the whole
truth, and
nothing but
the truth”
on two topics.
Sender
Receiver
Discuss 4 topics
“Maintain the
conversation”
“to not tell the
truth,
the whole
truth, and
nothing but
the truth”
on two topics.
Sender
Receiver
“Maintain the
conversation”
Discuss 4 topics
• 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
Word Count
170
160
150
140
Deception
130
Truth
120
110
100
Sender
Receiver
Word Count
170
28% increase
160
150
140
Deception
130
Truth
120
110
100
Sender
Receiver
%
words
9
8
deception
truth
7
6
5
4
3
2
1
0
Sender
Receiver
1st person singular
%
words
9
8
deception
truth
7
6
5
4
3
2
1
0
Sender
Receiver
1st person singular
%
words
9
8
deception
truth
7
6
5
4
3
2
1
0
Sender
Receiver
1st person singular
Sender
Receiver
2nd person
%
words
9
8
deception
truth
7
6
5
4
3
2
1
0
Sender
Receiver
1st person singular
Sender
Receiver
2nd person
Sender
Receiver
3rd person
%
words
Fewer 1st person singular
More 3rd person
9
8
deception
truth
7
6
5
4
3
2
1
0
Sender
Receiver
1st person singular
Sender
Receiver
2nd person
Sender
Receiver
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 phraselevel 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 load
Reduced coherence
Reduced use of exclusive terms
(e.g., never)
Cohmetrix
LIWC
Collaborative processes
Linguistic style matching
Question – answer patterns
Sequential discourse analysis
Auto-correlation
Sequence prediction
Keila & Skillicorn (2005)
More deceptive
Keila & Skillicorn (2005)
• 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 underused 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
Deception Research
1.
2.
3.
4.
5.
6.
Can people fake when instructed?
What is prevalence of faking?
What is the nature of faking?
Can faking be prevented or reduced?
Can faking be detected?
Can people avoid detection?
production
motivations
detection
Situational and Psychological Factors
Predicting Deception and its Detection:
Implications for Non-Cognitive Assessment
Jeff Hancock