A New Age of Communication: How
Different Relationships Influence Text
Messaging Behavior
As of 2014, 90% of people in the USA own a cell phone and
81% of their activity is attributed to text messaging.
18-29 = 98%
30-49 = 97%
60-54 = 88%
65+ = 74%
Its one of the few appliance that, when it goes missing, it has
an immediately impact on your life.
Cell Phones and Messaging
Have Taken Over Our Lives
(PEW Research Center, 2014)
So why is
text
messaging
so cool
bro?
C.A.P.
Control the transmission of
information
Arrange “face” to meet
presentational goals
Preserve aspects of
Personality, and disposition
New #
who dis?
It also allows recipients
to focus on
reciprocating the
emotions, or intentions
of the sender.
… And avoid social embarasment.
“
So what did I do for my study?
IV:
Sex
• Male
• Female
Relationship Type
• Family
• Friend
• Romantic interest
2x3 Mixed design
DV:
Words
Emotioncs
Abbreviations
Durations
N = 93
61F, 32M
Sona (n = 42)
21F, 21M
Online (n = 51)
40F, 11M
Age
18-23 (49.5%)
24-65+ (50.5%)
Table 1.
Mean Amounts for Words, Emoticons, Abbreviations, and Durations preferred by Males and
Females for Interaction Effects.
Males Females
_________________ __________________
Relationship Type M (SD) M (SD)
Family Relationship
Words 2.81 (.21) 3.28 (.15)*
Emoticons 1.43 (.23) 1.55 (.17)
Abbreviations 1.88 (.4) 2.71 (.28)*
Durations (minutes) 216.5 (66.6) 136.9 (48.2)
Friend Relationship
Words 2.75 (.26) 3.48 (.16)*
Emoticons 1.71 (.38) 2.63 (.28)*
Abbreviations 2.84 (.4) 2.96 (.26)
Durations (minutes) 130.9 (105.5)* 297.1 (76.4)
Romantic Relationship
Words 3.13 (.12) 3.31 (.14)
Emoticons 2.41 (.39) 2.45 (.28)
Abbreviations 2.5 (.4) 2.16 (.27)
Durations (minutes) 157.6 (69.7) 102.2 (50.5)
Females, Family, Friend, Words* F(1,91) = 5.635, p = .02, η2
= .058
Females, Family, Abbreviations* F(1,91) = 7.578, p = .007, η2
= .077
Females, Friend, Emoticon* F(1,91) = 7.78, p = .006, η2
= .079
Male, Friend, Duration* F(1,91) = 5.459, p = .022, η2
= .057
Table 2.
Mean Amounts for Words, Emoticons, Abbreviations, and Durations
preferred by Males and Females for Main Affects.
Words Emoticons Abbreviations Durations
IV M (SD) M (SD) M (SD) M (SD)
Relationship
Type
Family 3.1(.13) 1.49(.14)* 2.29(.24) 176.74(41.1)
Friend 3.1(.13) 2.17(.23) 2.91(.22)* 214(65.12)
Romantic 3.21(.12) 2.43(.24) 2.33(.23) 129.92(41.1)
Sex
Male 2.89(.18) 1.85(.29) 2.41(.33) 168.35(67.1)
Female 3.35(.13)* 2.22(.21) 2.61(.24) 178.77(48.58)
Female, Words* F(1,91) = 4.176, p = .044, η2
= .044.
Friend, Abbreviations* F(1,91) = 18.864, p < .000, η2
= .172
Family, Emoticons* F(1,91) = 24.713, p < .000, η2
= .214.
Place your screenshot
here
iPhone project
Show and explain your web, app or
software projects using these gadget
templates.
Table 3.
Mean Amounts of Words, Emoticons, Abbreviations, and Durations
Self-Coded by Males and Females.
Words Emoticons Abbreviations Durations
IV M (SD) M (SD) M (SD) M (SD)
Relationship
Type
Family 28.5 (5.6) 1.12 (.26) 1.74(.41) 535.24(171.01)
Friend 32.6(4.1) 1.41 (.4) 2.2 (.4) 282.34(97.94
Romantic 32.4(4.3) 2.24(.52) 2.7 (.758 80.848(27.3)*
Sex
Male 27.1(4.1) 1.2 (.3) 1.8 (.63) 362.22(91.42
Female 35.22(4.1) 2.03 (.5) 2.63 (.63) 236.73(93.67)
Relationship Type, Durations* F(1,39) = 6.895, p = .012, η2
= .15
Durations (In Hours)
Table 4.
Mean Amounts of Words, Emoticons, Abbreviations, and Durations Preferred by
Relationship Status.
Family Friend Romantic
Relationship Status M (SD) M (SD) M (SD)
Single/Dating
Words 2.93 (1.9) 2.8(.19) 3.23(.18)
Emoticons 1.28 (1.33) 2.18 (2.4) 2.5 (1.2)
Abbreviations 1.7(.15) 2.6 (.17) 2.3 (2.01)
Durations (minutes) 1.97.85(432.7) 143.55(379.34) 145.3(501.9)
Exclusive
Words 3.3 (.16) 3.5 (.17)* 3.3(.16)
Emoticons 1.7 (1.3) 2.4 (2.1) 2.4 (2.42)
Abbreviations 2.98 (2.43)* 3.17 (2.3) 2.3 (2.22)
Durations (minutes) 139.06 (329.6) 312.6 (716.9) 103.2(290.7)
Abbreviations, Family * F(1,91) = 8.431, p = .005, η2
= .085.
Words, Friends* F(1,91) = 5.712, p = .019, η2
= .059
# of Words
# of Emoticons
Words* F(1,40) = 8.084, p = .007, η2 = .168
Emoticons* F(1,40) = 7.889, p = .008, η2 = .165
Future Research
Thanks!
References
Angermuller, A., Maingueneau, D., & Wodak, R. (2014).  The discourse studies reader: Main currents in theory and analysis John.
 Philadelphia, PA:  Benjamins Publishing Company.
Derks D., Bos A. E. R., & Grumbkow J. K. (2008). Emoticons and online message interpretation. Social Science Computer Review,
26, 379-388.
Huang A. H., Yen D. C., & Zhang X. (2008).  Exploring the potential effects of emoticons.  Information Management, 45, 466-473.   
Herring, S. C., & Zelenkauskaite, A. (2009). Symbolic capital in a virtual heterosexual market: Abbreviation and insertion in Italian
iTV SMS. Written Communication, 26, 5-31.  DOI:10.1177/0741088308327911
Kato, Y., & Kato, S. (2015).  Reply speed to mobile text messages among Japanese college students:  When a quick reply is preferred
and a late reply is acceptable.  Computers In Human Behavior, 44, 209-219.
Ling, R., (2004). The mobile connection: The cell phone’s impact on society. San Francisco, CA: Morgan Kaufmann.
Lo, S. K. (2008).  The nonverbal communication functions of emoticons in computer-mediated communication.  CyberPsychology &
Behavior, 11, 595-597.
Oksman, V., & Turtiainen, J. (2004). Mobile communication as a social stage: Meanings of mobile communication in everyday life
among teenagers in Finland. New Media & Society, 6, 319–333.  DOI:10.1177/1461444804042518
PEW Research & Internet Life Project  (2014).  Mobile technology fact sheet: Highlights of the Pew Internet Project’s research
related to mobile technology.  Retrieved from http://www.pewinternet.org/fact-sheets/mobile-technology-fact-sheet/
Reid, F., & Reid, D. (2010).  The expressive and conversational affordances of mobile messaging.  Behavior & Information
Technology, 29, 3-22.
Thurlow, C. (2003).  Generation txt?  The sociolinguistics of young people's text-messaging.  Discourse Analysis Online.
 http://www.shu.ac.uk/daol/articles/open/2002-003/thurlow2002003.html
Wolf, A. (2000).  Emotional expression online:  Gender differences in emoticon use.  CyberPsychology & Behavior, 3, 827-833.

Robert Gaven

  • 1.
    A New Ageof Communication: How Different Relationships Influence Text Messaging Behavior
  • 2.
    As of 2014,90% of people in the USA own a cell phone and 81% of their activity is attributed to text messaging. 18-29 = 98% 30-49 = 97% 60-54 = 88% 65+ = 74% Its one of the few appliance that, when it goes missing, it has an immediately impact on your life. Cell Phones and Messaging Have Taken Over Our Lives (PEW Research Center, 2014)
  • 3.
    So why is text messaging socool bro? C.A.P. Control the transmission of information Arrange “face” to meet presentational goals Preserve aspects of Personality, and disposition New # who dis?
  • 4.
    It also allowsrecipients to focus on reciprocating the emotions, or intentions of the sender.
  • 5.
    … And avoidsocial embarasment.
  • 6.
    “ So what didI do for my study?
  • 7.
    IV: Sex • Male • Female RelationshipType • Family • Friend • Romantic interest 2x3 Mixed design DV: Words Emotioncs Abbreviations Durations N = 93 61F, 32M Sona (n = 42) 21F, 21M Online (n = 51) 40F, 11M Age 18-23 (49.5%) 24-65+ (50.5%)
  • 9.
    Table 1. Mean Amountsfor Words, Emoticons, Abbreviations, and Durations preferred by Males and Females for Interaction Effects. Males Females _________________ __________________ Relationship Type M (SD) M (SD) Family Relationship Words 2.81 (.21) 3.28 (.15)* Emoticons 1.43 (.23) 1.55 (.17) Abbreviations 1.88 (.4) 2.71 (.28)* Durations (minutes) 216.5 (66.6) 136.9 (48.2) Friend Relationship Words 2.75 (.26) 3.48 (.16)* Emoticons 1.71 (.38) 2.63 (.28)* Abbreviations 2.84 (.4) 2.96 (.26) Durations (minutes) 130.9 (105.5)* 297.1 (76.4) Romantic Relationship Words 3.13 (.12) 3.31 (.14) Emoticons 2.41 (.39) 2.45 (.28) Abbreviations 2.5 (.4) 2.16 (.27) Durations (minutes) 157.6 (69.7) 102.2 (50.5) Females, Family, Friend, Words* F(1,91) = 5.635, p = .02, η2 = .058 Females, Family, Abbreviations* F(1,91) = 7.578, p = .007, η2 = .077 Females, Friend, Emoticon* F(1,91) = 7.78, p = .006, η2 = .079 Male, Friend, Duration* F(1,91) = 5.459, p = .022, η2 = .057 Table 2. Mean Amounts for Words, Emoticons, Abbreviations, and Durations preferred by Males and Females for Main Affects. Words Emoticons Abbreviations Durations IV M (SD) M (SD) M (SD) M (SD) Relationship Type Family 3.1(.13) 1.49(.14)* 2.29(.24) 176.74(41.1) Friend 3.1(.13) 2.17(.23) 2.91(.22)* 214(65.12) Romantic 3.21(.12) 2.43(.24) 2.33(.23) 129.92(41.1) Sex Male 2.89(.18) 1.85(.29) 2.41(.33) 168.35(67.1) Female 3.35(.13)* 2.22(.21) 2.61(.24) 178.77(48.58) Female, Words* F(1,91) = 4.176, p = .044, η2 = .044. Friend, Abbreviations* F(1,91) = 18.864, p < .000, η2 = .172 Family, Emoticons* F(1,91) = 24.713, p < .000, η2 = .214.
  • 10.
    Place your screenshot here iPhoneproject Show and explain your web, app or software projects using these gadget templates.
  • 11.
    Table 3. Mean Amountsof Words, Emoticons, Abbreviations, and Durations Self-Coded by Males and Females. Words Emoticons Abbreviations Durations IV M (SD) M (SD) M (SD) M (SD) Relationship Type Family 28.5 (5.6) 1.12 (.26) 1.74(.41) 535.24(171.01) Friend 32.6(4.1) 1.41 (.4) 2.2 (.4) 282.34(97.94 Romantic 32.4(4.3) 2.24(.52) 2.7 (.758 80.848(27.3)* Sex Male 27.1(4.1) 1.2 (.3) 1.8 (.63) 362.22(91.42 Female 35.22(4.1) 2.03 (.5) 2.63 (.63) 236.73(93.67) Relationship Type, Durations* F(1,39) = 6.895, p = .012, η2 = .15
  • 12.
  • 13.
    Table 4. Mean Amountsof Words, Emoticons, Abbreviations, and Durations Preferred by Relationship Status. Family Friend Romantic Relationship Status M (SD) M (SD) M (SD) Single/Dating Words 2.93 (1.9) 2.8(.19) 3.23(.18) Emoticons 1.28 (1.33) 2.18 (2.4) 2.5 (1.2) Abbreviations 1.7(.15) 2.6 (.17) 2.3 (2.01) Durations (minutes) 1.97.85(432.7) 143.55(379.34) 145.3(501.9) Exclusive Words 3.3 (.16) 3.5 (.17)* 3.3(.16) Emoticons 1.7 (1.3) 2.4 (2.1) 2.4 (2.42) Abbreviations 2.98 (2.43)* 3.17 (2.3) 2.3 (2.22) Durations (minutes) 139.06 (329.6) 312.6 (716.9) 103.2(290.7) Abbreviations, Family * F(1,91) = 8.431, p = .005, η2 = .085. Words, Friends* F(1,91) = 5.712, p = .019, η2 = .059
  • 14.
    # of Words #of Emoticons Words* F(1,40) = 8.084, p = .007, η2 = .168 Emoticons* F(1,40) = 7.889, p = .008, η2 = .165
  • 15.
  • 16.
  • 17.
    References Angermuller, A., Maingueneau,D., & Wodak, R. (2014).  The discourse studies reader: Main currents in theory and analysis John.  Philadelphia, PA:  Benjamins Publishing Company. Derks D., Bos A. E. R., & Grumbkow J. K. (2008). Emoticons and online message interpretation. Social Science Computer Review, 26, 379-388. Huang A. H., Yen D. C., & Zhang X. (2008).  Exploring the potential effects of emoticons.  Information Management, 45, 466-473.    Herring, S. C., & Zelenkauskaite, A. (2009). Symbolic capital in a virtual heterosexual market: Abbreviation and insertion in Italian iTV SMS. Written Communication, 26, 5-31.  DOI:10.1177/0741088308327911 Kato, Y., & Kato, S. (2015).  Reply speed to mobile text messages among Japanese college students:  When a quick reply is preferred and a late reply is acceptable.  Computers In Human Behavior, 44, 209-219. Ling, R., (2004). The mobile connection: The cell phone’s impact on society. San Francisco, CA: Morgan Kaufmann. Lo, S. K. (2008).  The nonverbal communication functions of emoticons in computer-mediated communication.  CyberPsychology & Behavior, 11, 595-597. Oksman, V., & Turtiainen, J. (2004). Mobile communication as a social stage: Meanings of mobile communication in everyday life among teenagers in Finland. New Media & Society, 6, 319–333.  DOI:10.1177/1461444804042518 PEW Research & Internet Life Project  (2014).  Mobile technology fact sheet: Highlights of the Pew Internet Project’s research related to mobile technology.  Retrieved from http://www.pewinternet.org/fact-sheets/mobile-technology-fact-sheet/ Reid, F., & Reid, D. (2010).  The expressive and conversational affordances of mobile messaging.  Behavior & Information Technology, 29, 3-22. Thurlow, C. (2003).  Generation txt?  The sociolinguistics of young people's text-messaging.  Discourse Analysis Online.  http://www.shu.ac.uk/daol/articles/open/2002-003/thurlow2002003.html Wolf, A. (2000).  Emotional expression online:  Gender differences in emoticon use.  CyberPsychology & Behavior, 3, 827-833.