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Northwestern
University
People, Place & Time
The Daily Rhythms of Deception in
Interpersonal Text Messaging
Cornell
University
ICA 2013
London, UK
Lindsay
Reynolds
Jeremy
Birnholtz
Jeff
Hancock
Madeline
Smith
2
Butler Lies
• Often used to avoid social
interaction or explain a
communication failure
• Serve to maintain
relationships
• Depend on norms and
technological features
• Exploit ambiguities in
mediated communication
People
•Communication varies
by relationship types
and closeness
Agosto et al. 2012, Baym 2010
•Mixed findings about
who people lie most to
DePaulo & Kashy 1998, Cole 2001
•Butler lies told to
maintain relationships
Reynolds et al. 2011, Birnholtz et al. 2013
3
4
Who are lies and butler lies in
text messaging told to?
Research Question 1
5
Time
•Temporal context
affects perceptions
Goffman 1966
•Message timing can
effect relationships
Walther and Tidwell 1995
•People delay opening
and responding
Reynolds et al. 2011
"clock" by azmichelle on flickr
6
When are lies and butler lies in
text messaging told?
Research Question 2
Place
•Context important for
interpreting messages
•Location sharing apps
increasingly popular
Zickuhr 2012
•Decreased ambiguity
threatens butler lying
Birnholtz et al. 2010, Reynolds et al. 2013
7
8
How does location sharing affect
butler lying in text messaging?
Research Question 3
9
Method: Butler Messaging App
Study Procedure
1. Pre-study online materials
• Online consent form
• Deception Tutorial
• Download and install app
2. Use app for one week
• Email reminder mid-week
3. Post-study questionnaire
• Message logs with questions
• Experience with app
• Uninstall and debrief
10
Data and Coding
•3,963 sent messages
•959 butler messages (24.2%)
•230 deceptive messages (5.8%)
•89 butler lies (2.2%)
11
see#you#at#7:15#
I"did"not"like"
her"shirt"
RQ1: Relationships
•F(4,560.7) = 31.48, p<.001
•More messages sent to romantic partners than all
other categories (p<.001)
12
0"
5"
10"
15"
20"
25"
30"
35"
Acquaintance" Friend" Family" Roman8c" Other"
Percent'of'Text'Messages'
Rela2onship'Types'
Mean'Number'of'Text'Messages'Sent'per'Recipient''
RQ1: Relationships & Lying
•F(4,566.3)=1.05, p=.380
•No significant differences in rates of lying by
relationship type
13
0"
3"
6"
9"
12"
15"
Acquaintance" Friend" Family" Roman:c" Other"
Percent'of'Text'Messages'
Rela2onship'Types'
Percent'Lies'per'Recipient''
RQ1: Relationships & Butler Lying
14
0"
2"
4"
6"
8"
10"
Acquaintance" Friend" Family" Roman9c" Other"
Percent'of'Text'Messages'
Rela2onship'Types'
Percent'Butler'Lies'per'Recipient''
•F(4,568.5)=1.44, p=.219
•No differences in butler lying rates by relationship
type
RQ2:Time & Lying
15
RQ2:Time & Butler Lying
16
RQ3: Locations & Butler Lying
17
RQ3: Locations & Butler Lying
18
•χ2(1, N=3340) = 6.83, p<.01
•Locations shared with butler lies less frequently
than with other messages
Summary of Results
•More text messages sent to romantic partner
than other types of contacts
•Failed to find difference and lying and butler lying
to different types of contacts
•Butler lies sent at times of social coordination
•Butler lies were sent without locations more
often than other messages
19
Discussion
•Context matters: people, place and time
•New technological features can impact behavior
•Need more detailed studies of text messaging
•Butler Messaging app
20
Limitations & Future Work
•Self-reports of deception
•Potential self-selection bias
•Modified app included unfamiliar features
•Student sample
21
22
We thank Jon Culver, Daniel Haber, Jared Kass, Kate Pascucci, Weili Shi,
Mark Thomas and Jin Zhao for their valuable research assistance. Funding
was partially provided by NSF Grants IIS-0915081 and DGE-0824162.
People, Place & Time
The Daily Rhythms of Deception in Interpersonal Text Messaging
Lindsay
Reynolds
Jeremy
Birnholtz
Jeff
Hancock
Madeline
Smith
socialmedia.northwestern.edu sml.comm.cornell.edu

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ICA 2013: People, Place & Time: The Daily Rhythms of Deception in Text Messaging

  • 1. Northwestern University People, Place & Time The Daily Rhythms of Deception in Interpersonal Text Messaging Cornell University ICA 2013 London, UK Lindsay Reynolds Jeremy Birnholtz Jeff Hancock Madeline Smith
  • 2. 2 Butler Lies • Often used to avoid social interaction or explain a communication failure • Serve to maintain relationships • Depend on norms and technological features • Exploit ambiguities in mediated communication
  • 3. People •Communication varies by relationship types and closeness Agosto et al. 2012, Baym 2010 •Mixed findings about who people lie most to DePaulo & Kashy 1998, Cole 2001 •Butler lies told to maintain relationships Reynolds et al. 2011, Birnholtz et al. 2013 3
  • 4. 4 Who are lies and butler lies in text messaging told to? Research Question 1
  • 5. 5 Time •Temporal context affects perceptions Goffman 1966 •Message timing can effect relationships Walther and Tidwell 1995 •People delay opening and responding Reynolds et al. 2011 "clock" by azmichelle on flickr
  • 6. 6 When are lies and butler lies in text messaging told? Research Question 2
  • 7. Place •Context important for interpreting messages •Location sharing apps increasingly popular Zickuhr 2012 •Decreased ambiguity threatens butler lying Birnholtz et al. 2010, Reynolds et al. 2013 7
  • 8. 8 How does location sharing affect butler lying in text messaging? Research Question 3
  • 10. Study Procedure 1. Pre-study online materials • Online consent form • Deception Tutorial • Download and install app 2. Use app for one week • Email reminder mid-week 3. Post-study questionnaire • Message logs with questions • Experience with app • Uninstall and debrief 10
  • 11. Data and Coding •3,963 sent messages •959 butler messages (24.2%) •230 deceptive messages (5.8%) •89 butler lies (2.2%) 11 see#you#at#7:15# I"did"not"like" her"shirt"
  • 12. RQ1: Relationships •F(4,560.7) = 31.48, p<.001 •More messages sent to romantic partners than all other categories (p<.001) 12 0" 5" 10" 15" 20" 25" 30" 35" Acquaintance" Friend" Family" Roman8c" Other" Percent'of'Text'Messages' Rela2onship'Types' Mean'Number'of'Text'Messages'Sent'per'Recipient''
  • 13. RQ1: Relationships & Lying •F(4,566.3)=1.05, p=.380 •No significant differences in rates of lying by relationship type 13 0" 3" 6" 9" 12" 15" Acquaintance" Friend" Family" Roman:c" Other" Percent'of'Text'Messages' Rela2onship'Types' Percent'Lies'per'Recipient''
  • 14. RQ1: Relationships & Butler Lying 14 0" 2" 4" 6" 8" 10" Acquaintance" Friend" Family" Roman9c" Other" Percent'of'Text'Messages' Rela2onship'Types' Percent'Butler'Lies'per'Recipient'' •F(4,568.5)=1.44, p=.219 •No differences in butler lying rates by relationship type
  • 16. RQ2:Time & Butler Lying 16
  • 17. RQ3: Locations & Butler Lying 17
  • 18. RQ3: Locations & Butler Lying 18 •χ2(1, N=3340) = 6.83, p<.01 •Locations shared with butler lies less frequently than with other messages
  • 19. Summary of Results •More text messages sent to romantic partner than other types of contacts •Failed to find difference and lying and butler lying to different types of contacts •Butler lies sent at times of social coordination •Butler lies were sent without locations more often than other messages 19
  • 20. Discussion •Context matters: people, place and time •New technological features can impact behavior •Need more detailed studies of text messaging •Butler Messaging app 20
  • 21. Limitations & Future Work •Self-reports of deception •Potential self-selection bias •Modified app included unfamiliar features •Student sample 21
  • 22. 22 We thank Jon Culver, Daniel Haber, Jared Kass, Kate Pascucci, Weili Shi, Mark Thomas and Jin Zhao for their valuable research assistance. Funding was partially provided by NSF Grants IIS-0915081 and DGE-0824162. People, Place & Time The Daily Rhythms of Deception in Interpersonal Text Messaging Lindsay Reynolds Jeremy Birnholtz Jeff Hancock Madeline Smith socialmedia.northwestern.edu sml.comm.cornell.edu