1. 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

2. Types of deception Bald-faced lie Omission
Define: Omission is generally viewed as less severe

3. 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.

4. 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?

5. Omission A: I’m giving you ten. R: Ten bucks? So they gave you 20?
A: Ten is more than 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.

6. Non-strategic linguistic cues
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

7. 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

8. Modified ultimatum game
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

9. Method 102 dyads Given either $5/$30 endowment
LIWC: Linguistic Word Count Inquiry software

10. Lies (n = 7) Omission (n = 26) Truth (n = 69)
Variable M
First person singular (%)
8.53
5.67
6.32
Third person** (%)
0.94
0.00
0.17
Negative affect (%)
1.10
1.04
0.54
Profanity** (%)
0.27
0.05
Concreteness#
344.12
372.60
353.19
Words before verb
1.76
1.16
Type token ratio
0.79
0.91
0.90
Connectives
69.40
54.44
58.32
Note. * p < 0.05, ** p < .01
# Higher numbers indicate more concreteness.

11. Lies (n = 7) Omission (n = 26) Truth (n = 69)
Variable 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

12. Role of suspicion Lies Omission Truth Variable M Profanity (%)
0.64
0.00
0.23
No suspicion
0.18
Word count
62.33
31.87
100.11
76.00
30.09
32.50
Connectives
22.17
40.03
76.95
104.82
74.09
55.82

13. 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

14. Conclusions 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