1. Coye Cheshire & Andrew Fiore 4 April 2012 // Computer-Mediated Communication Intimate Relationships

2. 4/4/2012Computer-Mediated Communication — Cheshire & Fiore1 Romantic love — a timeless tradition?

3. Mediated meeting 4/4/2012Computer-Mediated Communication — Cheshire & Fiore2

4. 3 http://blog.modernmechanix.com/2008/04/08/boy-girl-computer/ 4/4/2012

5. Computer -Mediated Communi cation — Cheshire & Fiore 4 Thousands of boys and girls who’ve never met plan weekends together, for now that punch-card dating’s here, can flings be far behind? And oh, it’s so right, baby. The Great God Computer has sent the word. Fate. Destiny. Go-go-go. — Look Magazine, February 1966 http://blog.modernmechanix.com/2008/04/08/boy-girl-computer/ online 4/4/2012

6. Computer-Mediated Communication — Cheshire & Fiore5

7. 4/4/2012Computer-Mediated Communication — Cheshire & Fiore6 Pew online dating survey (2006) 63m know someone who has used a dating site 16m have used a dating site themselves 53m know someone who has gone on a date 7m have gone on a date themselves 29% of online adults think online daters desperate (but only 20% of those single and looking) 64% of online dating users think the large pool helps people find a better date 47% of all online adults concur

8. 4/4/2012Computer-Mediated Communication — Cheshire & Fiore7 designers Social shaping of technology

9. Online dating: The basics 4/4/2012Computer-Mediated Communication — Cheshire & Fiore8

10. 9 Fixed choice Free text Photo 4/4/2012Computer-Mediated Communication — Cheshire & Fiore

11. 4/4/2012Computer-Mediated Communication — Cheshire & Fiore10 Online dating profiles  Combination of categorical descriptors, free text self-description, and photos  Highly optimized self-presentations  Carefully selected detail  Unlimited time to craft  Exaggerations? Lies?  A lot of people lie a little (Hancock et al. 2007)  Do they reflect actual self? Ideal self?

12. Searching 4/4/201211Computer-Mediated Communication — Cheshire & Fiore

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15. Matching 4/4/201214Computer-Mediated Communication — Cheshire & Fiore

16. 4/4/201215Computer-Mediated Communication — Cheshire & Fiore

17. Conceptual lenses CMC Mate selection Searching/Matching Social networks Marriage markets 4/4/2012Computer-Mediated Communication — Cheshire & Fiore16

18. 4/4/2012Computer-Mediated Communication — Cheshire & Fiore17 ? Individuals Dyads Populations

19. Mate selection: Two perspectives Evolutionary psychology  Claims we seek and offer traits associated with reproductive success, so:  Women seek men with resources, signaled by age, wealth, education, height, etc.  Men seek women with fertility, signaled by youth, facial symmetry, muscle tone, etc. Assortative mating  Claims we partner with people like us (homophily).  Evident with regard to: Physical attractiveness, socioeconomic status, race, adult attachment style, personality traits, among others.  Yet sometimes it’s more complicated than just similarity. 18Computer-Mediated Communication — Cheshire & Fiore4/4/2012

20. Computer-Mediated Communication — Cheshire & Fiore19 7 10 4 8 5 2 86 7 3 9 5 6 8 5 3 2 6

21. 4/4/2012Computer-Mediated Communication — Cheshire & Fiore20 7 10 4 8 5 2 8 6 7 3 9 5 6 8 5 3 2 6

22. 4/4/2012Computer-Mediated Communication — Cheshire & Fiore21 7 seeks 10 for an awkward time “Marriage markets” — differential exchange Some points to ponder:  Why wouldn’t a 7 want a 10?  What stops us from trading up repeatedly?  Opportunity cost of staying with current mate?

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24. 4/4/2012Computer-Mediated Communication — Cheshire & Fiore23 The tyranny of choice, or: Gourmet jam is not a date

25. 4/4/2012Computer-Mediated Communication — Cheshire & Fiore24

26. 4/4/2012Computer-Mediated Communication — Cheshire & Fiore25 (Gupta & Singh 1982)

27. 4/4/2012Computer-Mediated Communication — Cheshire & Fiore26 The process of online dating

28. 4/4/2012Computer-Mediated Communication — Cheshire & Fiore27 Pieces of profiles: What predicts attractiveness?

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33. Photo × Text attractiveness 4/4/2012Computer-Mediated Communication — Cheshire & Fiore32 Photo high Photo med Photo low Women’s profilesMen’s profiles Text low Text med Text high Text low Text med Text high

34. 4/4/2012Computer-Mediated Communication — Cheshire & Fiore33 Strategic vs. authentic vs. aspirational self-presentation Anticipated future interaction? Actual self vs. ideal self? “Balancing accuracy and desirability”

35. 4/4/2012Computer-Mediated Communication — Cheshire & Fiore34

36. Participants from Ellison et al.  “In their profile they write about their dreams as if they are reality.”  “I’ve never known so many incredibly athletic women in my life!”  “I checked my profile and I had lied a little bit about the pounds, so I thought I had better start losing some weight so that it would be more honest.” 4/4/2012Computer-Mediated Communication — Cheshire & Fiore35

37. 4/4/2012Computer-Mediated Communication — Cheshire & Fiore36 Forming impressions in online dating  “Cognitive misers”: Making the most of limited cues  Social Information Processing (Walther)  Reciprocal re-use of what they notice in others

38. 4/4/2012Computer-Mediated Communication — Cheshire & Fiore37 Most people are not startlingly beautiful or magically attractive. But someone who seems just moderately nice — to most people — can flower under the imaginative attention of a lover’s eye. Not … because the lover is somehow gilding the other with fictitious charms; but because the kind of attention the lover brings allows less obvious qualities to be seen and appreciated. — Armstrong (2002)

39. 4/4/2012Computer-Mediated Communication — Cheshire & Fiore38 Deception? (Hancock et al. 2007)

40. 4/4/2012Computer-Mediated Communication — Cheshire & Fiore39 Deception? (Hancock et al. 2007)

41. 4/4/2012Computer-Mediated Communication — Cheshire & Fiore40 Deception? (Hancock et al. 2007)

42. 4/4/2012Computer-Mediated Communication — Cheshire & Fiore41 Honestly…(?)  And yet: in Gibbs et al. (2006), 94% said they had not intentionally misrepresented themselves.  87%: Doing so is not acceptable.  Still, they feel others are misrepresenting.  Why? Ellison et al. (2006) — Foggy mirrors, avoiding natural boundaries, portraying ideal selves…

43. 4/4/2012Computer-Mediated Communication — Cheshire & Fiore42 Is it deception? Or is it…  Misperception of self (foggy mirror)  Different readings of ambiguous labels  Self-enhancement (no intent to deceive)  Ideal self rather than actual self  Circumvention of technological constraints

44. 4/4/2012Computer-Mediated Communication — Cheshire & Fiore43 The peril (and promise) of ambiguity (“everything looks perfect from far away…”)

45. 4/4/2012Computer-Mediated Communication — Cheshire & Fiore44 Virtue in vagueness: Norah Jones The persona in her songs — let’s not call it Ms. Jones herself, because her life couldn't be this dull — might have lived practically anywhere in the developed world, at any time during the last century. Somehow Ms. Jones’s work has managed to make a virtue of vagueness. — The New York Times, Feb. 8, 2004, via Norton, Frost, & Ariely (2007)

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47. 4/4/2012Computer-Mediated Communication — Cheshire & Fiore46 I really like good music. I really like Billy Joel. ?

48. Norton, Frost, and Ariely (2007) 1.People think more knowledge = more liking 2.Actually, more traits = less liking 3.Similarity mediates the relationship in (2) 4.Dissimilarity cascades 5.Moving from the lab to real dates: Knowledge, liking, similarity before and after 4/4/2012Computer-Mediated Communication — Cheshire & Fiore47

49. Norton, Frost, and Ariely (2007) 1.People think more knowledge = more liking 2.Actually, more traits = less liking 3.Similarity mediates the relationship in (2) 4.Dissimilarity cascades 5.Moving from the lab to real dates: Knowledge, liking, similarity before and after 4/4/2012Computer-Mediated Communication — Cheshire & Fiore48

50. Norton, Frost, and Ariely (2007) 1.People think more knowledge = more liking 2.Actually, more traits = less liking 3.Similarity mediates the relationship in (2) 4.Dissimilarity cascades 5.Moving from the lab to real dates: Knowledge, liking, similarity before and after 4/4/2012Computer-Mediated Communication — Cheshire & Fiore49

51. Norton, Frost, and Ariely (2007) 1.People think more knowledge = more liking 2.Actually, more traits = less liking 3.Similarity mediates the relationship in (2) 4.Dissimilarity cascades 5.Moving from the lab to real dates: Knowledge, liking, similarity before and after 4/4/2012Computer-Mediated Communication — Cheshire & Fiore50

52. 4/4/2012Computer-Mediated Communication — Cheshire & Fiore51 Norton, Frost, & Ariely (2007)

53. Norton, Frost, and Ariely (2007) 1.People think more knowledge = more liking 2.Actually, more traits = less liking 3.Similarity mediates the relationship in (2) 4.Dissimilarity cascades 5.Moving from the lab to real dates: Knowledge, liking, similarity before and after 4/4/2012Computer-Mediated Communication — Cheshire & Fiore52

54. 4/4/2012Computer-Mediated Communication — Cheshire & Fiore53 “Dissimilarity cascades”

55. Norton, Frost, and Ariely (2007) 1.People think more knowledge = more liking 2.Actually, more traits = less liking 3.Similarity mediates the relationship in (2) 4.Dissimilarity cascades 5.Moving from the lab to real dates: Knowledge, liking, similarity before and after 4/4/2012Computer-Mediated Communication — Cheshire & Fiore54

56. 4/4/2012Computer-Mediated Communication — Cheshire & Fiore55 Norton, Frost, & Ariely (2007)

57. Fiore et al. Hypotheses: Pre-date/post-date H1: Participants will rate their dates less attractive on average after meeting face-to-face for the first time than before. H2: Levels of perceived commonality will be lower on average after face-to-face meeting than before. H3: Average ratings of how close a participant’s date is to his/her ideal for a partner will be lower after face- to-face meeting than before. 4/4/201256Computer-Mediated Communication — Cheshire & Fiore

58. Key questions and scales  How well have you gotten to know [name]?  How much do you have in common with [name]?  How close is [name] to your ideal for a partner?  Overall, how attractive do you find [name]?  How much is [name] someone you could see yourself: being friends with, dating casually, dating seriously, possibly something more?  Likert-type scale: 0 (not at all) – 6 (very much) 4/4/201257Computer-Mediated Communication — Cheshire & Fiore

59. p <.001 p <.01 *** ** *** 4/4/201258Computer-Mediated Communication — Cheshire & Fiore (Fiore et al.)

60. 59 onlinedatingmagazine.com 4/4/2012Computer-Mediated Communication — Cheshire & Fiore

61. 60 p <.01 p <.001 (Fiore et al.) 4/4/2012

62. Who seeks, contacts, and replies to whom? Computer -Mediated Communi cation — Cheshire & Fiore 614/4/2012

63. Age Computer -Mediated Communi cation — Cheshire & Fiore 624/4/2012

64. Age: Sought, contacted, replied to Computer -Mediated Communi cation — Cheshire & Fiore 63 n > 1,000,000 4/4/2012

65. Race Computer -Mediated Communi cation — Cheshire & Fiore 644/4/2012

66. Race: Preference analysis Computer -Mediated Communi cation — Cheshire & Fiore 65 n > 1,000,000 Proportion of users who sought and contacted only people of the same race by age and sex 4/4/2012

67. Race: Contact analysis Computer -Mediated Communi cation — Cheshire & Fiore 66 n > 1,000,000 Average proportion of contacts to same race by age and sex 4/4/2012

68. Religion Computer -Mediated Communi cation — Cheshire & Fiore 674/4/2012

69. Religion: Preference analysis Computer -Mediated Communi cation — Cheshire & Fiore 68 n > 1,000,000 4/4/2012

70. Religion: Contact analysis Computer -Mediated Communi cation — Cheshire & Fiore 69 n > 1,000,000 4/4/2012

71. Who replies? Computer -Mediated Communi cation — Cheshire & Fiore 704/4/2012

72. Computer -Mediated Communi cation — Cheshire & Fiore 714/4/2012

73. How late is too late to reply?  Median time to first reply: 16.1 hrs for a man contacted by a woman 19.2 hrs for a woman contacted by a man  Chance of follow-up by initiator declines ~0.7% per day that recipient waits to reply. Computer -Mediated Communi cation — Cheshire & Fiore 724/4/2012