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Bit By Bit
: Social Research in the Digital Age
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Àkọsọ
1 Ọrọ Iṣaaju
1.1 An inki abawọn
1.2 Kaabo si oni ori
1.3 Research design
1.4 Awọn akori yi iwe
1.4.1 Readymades ati Custommades
1.4.2 Ayedero lori complexity
1.4.3 Ethics nibi gbogbo
1.5 Ìsọrí-iwe
2 wíwo ihuwasi
2.1 Iṣaaju
2.2 Big data
2.3 wọpọ abuda kan ti ńlá data
2.3.1 Abuda ti o wa ni gbogbo ti o dara fun iwadi
2.3.1.1 Big
2.3.1.2 Nigbagbogbo-on
2.3.1.3 Non-ifaseyin
2.3.2 Abuda ti o wa ni gbogbo buburu fun iwadi
2.3.2.1 pe
2.3.2.2 inaccessible
2.3.2.3 Non-asoju
2.3.2.4 Drifting
2.3.2.5 Algorithmically tì
2.3.2.6 ni idọti
2.3.2.7 kókó
2.4 Research ogbon
2.4.1 kika ohun
2.4.1.1 taxis ni New York City
2.4.1.2 Ore Ibiyi laarin omo ile
2.4.1.3 ihamon ti awujo media nipa awọn Chinese ijoba
2.4.2 asọtẹlẹ ati nowcasting
2.4.3 Approximating adanwo
2.4.3.1 Adayeba adanwo
2.4.3.2 tuntun
2.5 Ipari
imọ ÀFIKÚN
siwaju asọye
akitiyan
3 béèrè ibeere
3.1 Iṣaaju
3.2 béèrè vs. wíwo
3.3 Awọn lapapọ iwadi aṣiṣe ilana
3.3.1 oniduro
3.3.2 Measurement
3.3.3 Iye
3.4 Tani lati beere
3.4.1 iṣeeṣe iṣapẹẹrẹ: data gbigba ati data onínọmbà
3.4.2 Non-iṣeeṣe ayẹwo: weighting
3.4.3 Non-iṣeeṣe ayẹwo: awọn ayẹwo tuntun
3.5 New ona ti béèrè ìbéèrè
3.5.1 Ecological momentary igbelewọn
3.5.2 Wiki iwadi
3.5.3 Gamification
3.6 iwadi ti sopọ si miiran data
3.6.1 ni ariwo béèrè
3.6.2 idarato bibeere
3.7 Ipari
imọ ÀFIKÚN
siwaju asọye
akitiyan
4 yen adanwo
4.1 Iṣaaju
4.2 Ki ni adanwo?
4.3 meji mefa ti adanwo: lab-oko ati afọwọṣe-oni
4.4 Gbigbe kọja rọrun adanwo
4.4.1 Wiwulo
4.4.2 mu agbara pọ si ti itọju ipa
4.4.3 sise
4.5 Ṣiṣe o ṣẹlẹ
4.5.1 kan se o ara
4.5.1.1 Lo tẹlẹ agbegbe
4.5.1.2 Kọ ara rẹ ṣàdánwò
4.5.1.3 Kọ ara rẹ ọja
4.5.2 Ẹnìkejì pẹlu awọn alagbara
4.6 Advice
4.6.1 Ṣẹda odo ayípadà iye owo data
4.6.2 Rọpo, liti, ati Din
4.7 Ipari
imọ ÀFIKÚN
siwaju asọye
akitiyan
5 Ibi ifowosowopo
5.1 Iṣaaju
5.2 Human iṣiro
5.2.1 Galaxy Zoo
5.2.2 Crowd-ifaminsi ti oselu manifestos
5.2.3 Ipari
5.3 Open awọn ipe
5.3.1 Netflix Prize
5.3.2 Foldit
5.3.3 Ẹlẹgbẹ-si-itọsi
5.3.4 Ipari
5.4 Pin data gbigba
5.4.1 eBird
5.4.2 PhotoCity
5.4.3 Ipari
5.5 Nse ara rẹ
5.5.1 ru olukopa
5.5.2 idogba mu agbara pọ si
5.5.3 Idojukọ ifojusi
5.5.4 ṣiṣẹ iyalenu
5.5.5 Jẹ asa
5.5.6 Ik oniru imọran
5.6 Ipari
siwaju asọye
akitiyan
6 ethics
6.1 Iṣaaju
6.2 Meta apeere
6.2.1 imolara Contagion
6.2.2 Lenu, seése, ati Time
6.2.3 Encore
6.3 Digital ti o yatọ si
6.4 Mẹrin agbekale
6.4.1 Ọwọ fun Eniyan
6.4.2 Beneficence
6.4.3 Justice
6.4.4 Ọwọ fun ofin ati Public Interest
6.5 Meji asa nílẹ
6.6 Areas ti isoro
6.6.1 fun èrò
6.6.2 Oye ki o si Ṣiṣakoṣo awọn iroyin eleko ewu
6.6.3 Asiri
6.6.4 Ṣiṣe ipinu ninu awọn oju ti aidaniloju
6.7 Practical awọn italolobo
6.7.1 The IRB ni a pakà, ko kan aja
6.7.2 Fi ara rẹ ni gbogbo eniyan miran ká bata
6.7.3 ro ti iwadi ethics bi lemọlemọfún, ko ọtọ
6.8 Ipari
itan ÀFIKÚN
siwaju asọye
akitiyan
7 Awọn ojo iwaju
7.1 Nwa foward
7.2 Awọn akori ti awọn ojo iwaju
7.2.1 The blending ti Readymades ati Custommades
7.2.2 alabaṣe-ti dojukọ data gbigba
7.2.3 Ethics ni iwadi design
7.3 Back to ibẹrẹ
Acknowledgments
jo
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4
yen adanwo
4.1 Iṣaaju
4.2 Ki ni adanwo?
4.3 meji mefa ti adanwo: lab-oko ati afọwọṣe-oni
4.4 Gbigbe kọja rọrun adanwo
4.4.1 Wiwulo
4.4.2 mu agbara pọ si ti itọju ipa
4.4.3 sise
4.5 Ṣiṣe o ṣẹlẹ
4.5.1 kan se o ara
4.5.1.1 Lo tẹlẹ agbegbe
4.5.1.2 Kọ ara rẹ ṣàdánwò
4.5.1.3 Kọ ara rẹ ọja
4.5.2 Ẹnìkejì pẹlu awọn alagbara
4.6 Advice
4.6.1 Ṣẹda odo ayípadà iye owo data
4.6.2 Rọpo, liti, ati Din
4.7 Ipari
imọ ÀFIKÚN
siwaju asọye
akitiyan
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