Evidence for the Pinocchio effect:
Linguistic differences between lies,
deception by omission, and truth
Lyn M. Van Swol & Michael T. Braun
University of Wisconsin-Madison
Deepak Malhotra
Harvard Business School
Types of deception
• Bald-faced lie
• Omission
Lie
• A: Um, I’m giving you a dollar fifty.
• R: You’re giving me a dollar fifty. How much did they
give you?
• A: Three dollars.
• R: You’re lying. You know why?
• A: Why?
• R: Because I heard her say she gave you five bucks.
• A: Well, that’s part of her experiment, she’s trying to
fuck with you. Probably shouldn’t say that with the
camera..whatever.
Omission
• A: Okay, so I’m allocating 10 dollars to you, so I
don’t know if you want 10 dollars or not.
• R: That’s fine.
• A: I don’t know if you can deal with that.
Okay, so how are you doing?
Omission
•
•
•
•
•
•
•
•
•
A: I’m giving you ten.
R: Ten bucks? So they gave you 20?
A: Ten is more than 7.50. So I figured…
R: Yeah. The only thing I’m interested in is if they gave you
thirty or not.
A: Only if what?
R: The only thing I’d have a problem with is if they gave you
30 or not. And I know you wouldn’t dick me over, so.
A: And of course, we’d all figure this out later.
R: What?
A: We could figure this all out later.
Non-strategic linguistic cues
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•
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Pronoun use: first person and third person
Negative emotion words and suspicion
Swearing and suspicion
Higher cognitive load: concreteness, sentence
complexity, type-token ratio, connectives
Strategic linguistic cues
• Word count
– Pinocchio effect: greater words when reality
cannot be verified/no concealment goals
– Omission and reduced word count: concealment
goal
• Causation words
Modified ultimatum game
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•
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Endowment amount
Roles: Allocator/Recipient
Recipient only has knowledge of range of values
Allocator allocates endowment between self and
recipient
• Recipient can accept or reject offer
• If rejected, allocator gets nothing and recipient
gets a default amount of 25% of endowment
• Interactions videotaped and transcribed
Method
• 102 dyads
• Given either $5/$30 endowment
• LIWC: Linguistic Word Count Inquiry software
Lies (n = 7)
Variable
Omission (n = 26) Truth (n = 69)
M
M
M
8.53
5.67
6.32
0.94
0.00
0.17
Negative affect (%)
1.10
1.04
0.54
Profanity** (%)
0.27
0.00
0.05
344.12
372.60
353.19
Words before verb
1.76
1.16
1.16
Type token ratio
0.79
0.91
0.90
Connectives
69.40
54.44
58.32
First person singular (%)
Third person** (%)
Concreteness#
Note. * p < 0.05, ** p < .01
#
Higher numbers indicate more concreteness.
Lies (n = 7)
Variable
Omission (n = 26) Truth (n = 69)
M
M
M
Word Count**
70.14
31.12
41.58
Causation* (%)
2.50
0.43
1.31
Money** (%)
5.35
1.82
1.05
Note. * p < 0.05, ** p < .01
Role of suspicion
Lies
Variable
Omission
Truth
M
M
M
Suspicion
0.64
0.00
0.23
No suspicion
0.00
0.00
0.18
Suspicion
62.33
31.87
100.11
No suspicion
76.00
30.09
32.50
Suspicion
22.17
40.03
76.95
No suspicion
104.82
74.09
55.82
Profanity (%)
Word count
Connectives
Multinomial logistic regression to
predict offer type
Deception Type = Lie
Third person pronouns (%) B = 0.95*
Number words (%) B = 0.45**
Note. * p < .05, ** p < .01
Conclusions
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Importance of context with word count
Without verifiable reality: Pinocchio effect
With concealment goal: reduced word count
Replicated past research with third person
pronouns
• Tentative results about profanity
• Negative emotion words and suspicion