WHY THIS PAPER?

“손바닥안의중매쟁이” - 해외사례

온라인데이팅서비스는해외에서보다보편적행동

△미국부부 3쌍중 1쌍은온라인을통해만난다(National Academy of

Sciences)

△미국성인의 60%는온라인데이팅이이성을만나기좋은방법이라고생각하

며

50%는온라인데이팅이나에게더잘맞는이성을찾아준다고생각한다(Pew

Research Center)

△미국싱글들약 5400만명중 4900만명이온라인데이팅서비스를사용한경

험

이있다(Statistic Brain)

△온라인으로서로를먼저알아보면서시작하는결혼이이혼율이더낮다

(eHarmony) 등등이다.http://m.news.naver.com/read.nhn?mode=LSD&mid=sec&sid1=110&oid=008&aid=0003599660

WHY THIS PAPER?

http://m.news.naver.com/read.nhn?mode=LSD&mid=sec&sid1=101&oid=056&aid=0000020287http://www.diodeo.com/news/view/1208374

“손바닥안의중매쟁이” - 국내사례

WHY THIS PAPER?

speed dating concept developed by researchers @Newcastle University

to explore how the informaton gathered by devices

can be applied to social setting

CONCEPT: Metadating

speed dating concept developed by researchers @Newcastle University

to explore how the informaton gathered by devices

can be applied to social setting

Metadating

CONCEPT

s

# PERSONAL DATA

# QUANTIFIED SELF

# LIVED INFORMATICS

(개념) “lived informatics” —> (적용) social reality of a “data- driven life *”

Overview

* personal data is used conversationally

to communicate and illustrate identity

• representing & curating [data profiles] in new ways

• beyond a focus on purely rational & analytics relationship with quantifed self

introduction —> background —> method —> findings —> conclusion

“quantifed self”

Engagement with scenarios & prototypes

Methodology

organized workshop as a genuine speed dating event

where single participants “dated” each other

based on “data profiles”

사용 X

1

2 Participation in role playing, theatre, and improvisation or design fictions

❶ Engagement with scenarios & prototypes

❷ Participation in role playing, theatre, and improvisation or design fictions

Methodology

organized workshop as a genuine speed dating event

where single participants “dated” each other

based on “data profiles”

사용 X

11 participants

Saturday night

@ University Campus

single

1 participant had experience of speed dating evetnts

other had used dating sites & apps (Tinder)

participants aged between 22 - 40 (mean age of 32)

3 hours

4 activities

men seeking women or women seeking men

Methodology

Data Profiles

Myself (Left): Blank profile with strucutred Questions

My data (Right): Open ended graphs & tables

Aim: help visualization of the data

overview

Methodology

Data Profiles

Myself (Left): Blank profile with strucutred Questions

My data (Right): Open ended graphs & tables

A5 용지 3장

Myself

- strcutured biographic

details

ex.

waking pace, heart rate,

furthest distance

travelled from home, # of

listens to favorite songs,

top 3 lists of mussic/ film

My dataMyself

Empty graphs,

tables and

visualization to

complete

Participants decide what they recorded, and

how accurate or honest they were with what

they shared

EXAMPLE 1

Methodology

Data Profiles

EXAMPLE 2

Methodology

Data Profiles

Activity 1: First impression

Particpants reads each others’ first impression of anonymous profiles

Activity 1: First impression

Particpants reads each others’ first impression of anonymous profiles

2 mixed gender groups

intent:

- lossely replicate the experience of online dating juding someone

based on their profile without meeting them

Q:

would you like to meet these people?

what’s missing from these profiles?

what’s attractive or unattractive in this data?

Activity 2: Speed dating

2 couples “meatadating,” with data profiles

Activity 2: Speed dating

2 couples “meatadating,” with data profiles

• 2 rounds of 4 with a break in-between

• gender balance

• - women would enjoy 7 dates while men

would enjoy 4

laid out data profiles on table for the 1st date

• total 28 dates 4 minutes each

Activity 3: Clustering data

Individual charts, graph lists, etc that all the data people had drawn

ASKED

what different categories & types did people collect

what type of data does and does not did people collect?

participants were provided 2 descriptions of personas

they created and presented both an ideal and flawed profile for them

Activity 4: Ideal profiles

For the final activity,

asking about what they think about what type of data might fit each profile

- 4 male, 4 female

- 6 out of 8 participated the whole event

- 2 out of 8 expressed interest but dropped out

Follow up interviews

several months later,

8 follow up interviews were conducted

to find out why they pulled out of the event

discuss their perceptions of the data profiles w/o attending the event

Findings

참가자들이비어있는공간과그래프등을다양하게활용해서자신의 live informatics를표현함

1주일동안먹은음식 다녀온여행

어떤식의집/가구스타일으로꾸며놓았는지

Findings

1주일동안한운동한경력(몇마일뛰었는지)

1주일동안한활동

지난해동안 “만든것” 혹은 “쓴것”들

fitbit step tracker의정확한스텝수

Findings

1주일동안한운동한경력(몇마일뛰었는지)

1주일동안한활동

지난해동안 “만든것” 혹은 “쓴것”들

fitbit step tracker의정확한스텝수88 separate examples of data

- 10 pie charts

- 14 graphs

- 6 maps / travel

- 50 charts/ dots (to record daily events)

data profiles 에대해서,

Findings

1주일동안한운동한경력(몇마일뛰었는지)

1주일동안한활동

지난해동안 “만든것” 혹은 “쓴것”들

fitbit step tracker의정확한스텝수

quantified self

- recording sleep

- consumption of food & drink

- exercise, cycling and steps

unusual

- calling mom over the week

- eating specific food (muesli)

- cooking days

- mental & phsyical aitivty

- routines and activities - sharing vices (악)

ex. alcohol, coffee, chocolate, cake and biscuits

- conversing around & with data

ticket for talk : helping invidual to initiate

conversation and structured encounters

conversational strategies

- read data out loud

- dates

- asking questions

- explaining the context

- turn- taking and comparison

- compliments of data

comparison inherent to data (and dating)

playing around with data

avoiding, defending, and downplaying data

Findings

curiosity rather than anaylsis or presentation

exploiting ambiguity and explaining the context

comparison inherent to data (and dating)

playing around with data

avoiding, defending, and downplaying data

Findings

curiosity rather than anaylsis or presentation

exploiting ambiguity and explaining the context

hand-grawn graphs 여서, 참여자들이좀더 expressive 하게표현하고,

데이타에대한해석을해주었다.

몇몇의참여자들은 unusual & interesting 한 data 기록함

또다른참여자들은 honest & accurate 한 data를기록함

1

2

3

# Lived informatics

Conclusions

human value & experience

ticket for talk *a dry &

mechanical

speculative & future focused

“Metadating”

# Quantified Self

한 personal data 이아닌

서로의데이타를분석하기보다커플들이처음대화를시작하는데도움을줌

*

*이례적인셋업된환경임에도불구하고,

사람들은 (아무대화의토픽)에대해서말하는데문제없었음.

Takeaway

어떤데이터가 (깜찍하게) 재사용되어서, 사람한테제공될수있는지?

1

2

3

데이터는수집하고해석하기나름

질적연구여서데이터가숫자가아니라고, 유익하지않고별로인게아니다

dry 하지않고“playful” 하게풀수있음