imisebenzi

key:

  • isidanga wobunzima: ulula lula , eliphakathi phakathi , nzima lukhuni , kakhulu kakhulu kakhulu kakhulu
  • kufuna zezibalo ( kufuna zezibalo )
  • kufuna nokhowudo ( kufuna nokhowudo )
  • nokuqokelelwa kwedatha ( nokuqokelelwa kwedatha )
  • ndiwathandayo ( endiythanda kakhulu )

  1. [ lukhuni , kufuna zezibalo ] Kwisahluko, ndaba ezihle kakhulu malunga post-abahlulwe. Nangona kunjalo, oko akuthethi akusoloko ukuphucula umgangatho uqikelelo. Ukwakha imeko apho anokuthumela-abahlulwe ziyakwazi ukunciphisa umgangatho uqikelelo. (Kuba uthsuphe, bona Thomsen (1973) ).

  2. [ lukhuni , nokuqokelelwa kwedatha , kufuna nokhowudo ] Design kunye kuqhuba isaveyi non-linokuba on Amazon MTurk ukuze ubuze malunga ubunini umpu ( "Ngaba, okanye nabani na endlwini yakho, nompu, umpu okanye ngomva? Ingaba wena okanye omnye umntu kwikhaya lakho?") Kwaye ukuziphatha yolawulo lwemipu ( "Yintoni ocinga ukuba ibalulekile-ngaphezulu ukukhusela ilungelo Merika banemipu, okanye ukulawula ubunini umpu?").

    1. Ingaba uphando lwakho kuthabatha ixesha elide kangakanani? Ingaba ibiza malini? Njani labantu isampuli yakho thelekisa kwi amanani abantu bebonke US?
    2. Yintoni na uqikelelo ekrwada kobunini umpu usebenzisa intshumayelo yenu?
    3. Obulungele non-nokumela kwiisampula yakho usebenzisa post-abahlulwe okanye enye indlela. Ngoku yintoni na uqikelelo kobunini umpu?
    4. musa liqikelela thelekisa njani kuqikelelo akutshanje iPew Research Center? Ucinga ukuba ukucacisa nokungangqinelani, ukuba kukho nayiphi na?
    5. Phinda lo msebenzi 2-5 isimo sengqondo yolawulo lwemipu. ukuba zahluke njani iziphumo zakho?

  3. [ kakhulu kakhulu , nokuqokelelwa kwedatha , kufuna nokhowudo ] Goel noogxa (2016) lenze uphando non-linokuba-based ebandakanya imibuzo 49 multiple-choice attitudinal avela Jikelele Social Survey (GSS) kwaye khetha uphando ngokuthi iPew Research Center on Amazon MTurk. Bakugqiba nyenyisa ngenxa non-nokumela data usebenzisa imodeli-based post-abahlulwe (Mnu P), uze uthelekise ngawoqikelelo oluhlaziyiweyo nabo kuqikelelwa usebenzisa iisaveyi GSS / Pew ezinokwenzeka-based. Kuqhuba isaveyi ofanayo MTurk kwaye sizame senze ngokufanayo kuMfanekiso 2A Figure 2b ngokuthelekisa liqikelela olulungisiweyo kunye noqikelelo ukususela kwimijikelo zakutshanje ze GSS / Pew (Funda isiHlomelo Table A2 uluhlu lwemibuzo 49).

    1. Thelekisa umahluko iziphumo zakho iziphumo kwi iPew kunye GSS.
    2. Thelekisa umahluko iziphumo zakho iziphumo ezivela kwisaveyi MTurk in Goel, Obeng, and Rothschild (2016) .

  4. [ phakathi , nokuqokelelwa kwedatha , kufuna nokhowudo ] Izifundo ezininzi zisebenzisa amanyathelo self-ingxelo mobile data umsebenzi yefowuni. Esi sicwangciso umdla apho abaphandi bakwazi ukuthelekisa ukuziphatha self-ingxelo yokuziphatha ezifakiweyo (jonga umzekelo, Boase and Ling (2013) ). izimo ezimbini eziqhelekileyo ukubuza nibiza kwaye ngefowuni, kwaye izakhelo ezimbini ixesha eziqhelekileyo malunga ngala "izolo" kwaye "kule veki iphelileyo."

    1. Phambi ukuqokelela nayiphi na idata, nguwuphi kule self-ngxelo amanyathelo Ucinga ukuba ibe yechaneke ngaphezulu? Ngoba?
    2. Ukuqesha 5 abahlobo bakho ukuba babe kuphando yakho. Nceda zishwankathela ngokufutshane zavavanywa njani kwaba bahlobo 5. Ngaba le nkqubo isampulu ukubaphembelela ucalu ezithile liqikelela?
    3. Nceda ucele kulandelayo micro-uphando:
    • "Ozisebenzisileyo Kukangaphi ifowuni ephathwayo ukubiza abanye izolo?"
    • "Yona njani imiyalezo emininzi izolo?"
    • "Ozisebenzisileyo Kukangaphi ifowuni yakho mobile ukubiza abanye imihla esixhenxe yokugqibela?"
    • "Amaxesha amaninzi wenza ukuba usebenzise ifowuni yakho ukuthumela okanye ukufumana imiyalezo / SMS ngemihla ezisixhenxe yokugqibela?" Emva kokuba uphando lugqityiwe, cela ukukhangela iinkcukacha zabo usebenziso njengoko ezilogwe yi ngefowuni okanye inkonzo yabo umboneleli.
    1. ntoni usebenziso self-ngxelo thelekisa Indlela nkcukacha? Yeyiphi zichanekileyo, nto incinane ichanile?
    2. Ngoku ekuhlanganiseni data ukuba obuziqokelele idatha kwezinye abantu eklasini yakho (ukuba wenza lo msebenzi eklasini). Ngesi dataset ezinkulu, phinda inxalenye (d).

  5. [ phakathi , nokuqokelelwa kwedatha ] Schuman kunye Presser (1996) bathi imiyalelo mbuzo azilithetheleli iintlobo ezimbini ubudlelwane phakathi imibuzo: Imibuzo yinxalenye-yinxalenye apho lo mibuzo mibini kumgangatho ofanayo Okukodwa (umzekelo amanqaku abaviwa ezimbini kamongameli); kunye nemibuzo yinxalenye-wonke apho umbuzo jikelele lulandelayo umbuzo kakhulu ethile (umzekelo, becela "Waneliseke kangakanani umsebenzi wenu?" elilandelwe ngu "Waneliseke kangakanani bubomi bakho?").

    Ke ngakumbi ubeluphawu iindidi ezimbini isiphumo umbuzo umyalelo: iziphumo ngokufanayo xa iimpendulo kumbuzo kamva ziziswa kufutshane (kunokuba ngenye indlela) kwi benikelwe umbuzo ngaphambili; kwahluke iziphumo xa kukho umahluko omkhulu phakathi iimpendulo kwimibuzo emibini.

    1. Yenza isibini imibuzo inxalenye-yinxalenye ocinga ukuba iya kuba nempembelelo enkulu umbuzo umyalelo, isikere yinxalenye-wonke imibuzo ocinga ukuba iya kuba nefuthe umyalelo elikhulu, kwaye enye iperi imibuzo ocinga Akukhathaliseki umyalelo wakhe. Yenza lamava uphando kwi MTurk ukuvavanya imibuzo yakho.
    2. yayinkulu njani isiphumo yinxalenye-nxaxheba ukuba bakwazi ukuyila? Ngaba guquki okanye umahluko isiphumo?
    3. yayinkulu njani isiphumo yinxalenye-wonke ukuba bakwazi ukuyila? Ngaba guquki okanye umahluko isiphumo?
    4. Ngaba kukho umyalelo isiphumo umbuzo kwisibini yakho apho akazange acinge umyalelo azilithetheleli?

  6. [ phakathi , nokuqokelelwa kwedatha ] Ukwakha kumsebenzi Schuman kunye Presser, Moore (2002) uchaza njengomlinganiso eyahlukileyo isiphumo umbuzo umyalelo: isongezo, kunye yeyeemeko apho. Nangona uthelekiso kunye ukungqinelana neziphumo ziveliswa njengesiphumo uvandlakanyo abaphenduli 'lwezinto ezimbini ngokunxulumene kwabanye, wongezelelo ngamnye kunye neziphumo yeyeemeko ziveliswa xa wenza abaphendule olubuthathaka kakhulu-sikhokelo ezinkulu ngaphakathi apho imibuzo ebuziweyo. Funda Moore (2002) , ke ngoko bayile baze benze uvavanyo uphando kwi MTurk ukubonisa isongezo, okanye yeyeemeko iziphumo.

  7. [ lukhuni , nokuqokelelwa kwedatha ] Christopher Antoun noogxa (2015) laqhuba uphando sithelekisa iisampuli lula efunyenwe ezine ezahlukeneyo online imithombo ukugaya: MTurk, Craigslist, Google AdWords kunye Facebook. Yila uphando elula nokuqesha nxaxheba kwimithombo ubuncinane ezimbini ezahlukeneyo online ukugaya (inokuba imithombo eyahlukeneyo ukusuka imithombo ezine ezisetyenziswa Antoun et al. (2015) ).

    1. Thelekisa iindleko amalizo nganye, ngokwemiqathango imali nexesha, phakathi kwimithombo eyahlukeneyo.
    2. Thelekisa ukwakhiwa kweesampula olufunyenwe kwimithombo eyahlukeneyo.
    3. Thelekisa umgangatho data phakathi iisampuli. Kuba iingcinga malunga ukulinganisa ngendlela esemgangathweni data evela abaphenduli, bona Schober et al. (2015) .
    4. Yintoni na umthombo ekhethwayo yakho? Ngoba?

  8. [ phakathi ] YouGov, umntu esekelwe kwi-intanethi lemfuna ngokuqinileyo, kuqhutywa ngokweentloko ekhompyutheni ligqiza malunga 800.000 baphendula UK kwaye asetyenziselwa uMnu P. ukuqikelela isiphumo EU Uvoto (oko kukuthi, Brexit) apho lwabavoti UK ukuvota nokuba ukuhlala okanye ashiye European Union.

    Inkcazelo eneenkcukacha imodeli statistical YouGov yeyona apha (https://yougov.co.uk/news/2016/06/21/yougov-referendum-model/). Kalukhuni ukuthetha, YouGov Ulwahlulo lwabavoti ngokwendidi ngokusekelwe 2015 unyulo jikelele ukhetho ivoti, ubudala, iziqinisekiso, isini, umhla ndlebe, kwakunye elisemthethweni abaphila kulo. Okokuqala, bona basebenzisa data eqokelelwe panelists YouGov ukuqikelela, phakathi kwabo ngubani ukuvota, inani labantu yohlobo lwabavoti ngamnye banenjongo ukuvota weKhefu. Baye baqikelela kaGrant uhlobo lwabavoti ngalinye ngokusebenzisa 2015 British Study Election (BES) lwangaphaya konyulo ubuso ngobuso phando, kungqinisiswa enithe evela kwizixa lonyulo. Ekugqibeleni, baqikelele bangaphi abantu kukho kuhlobo ngalunye ngumvoti kwabavoti esekelwe kuBalo lwakutsha and Annual Population Survey (inkcazelo Ukongeza evela BES, YouGov uphando data ehlabathini unyulo jikelele, kwaye ulwazi vanhu vo ezininzi iqela ngalinye yonyulo nganye).

    Kwiintsuku ezintathu ngaphambi kokuba kuvotwe, YouGov wabonisa okhokelayo point ezimbini Zelivu. Ngobusuku yokuvota, yokuvota wabonisa kufutshane kakhulu ukubiza (49-51 Hlalani). Lokugqibela uphando kwi-mini-kwangaphambili 48/52 baxhasa Hlala (https://yougov.co.uk/news/2016/06/23/yougov-day-poll/). Enyanisweni, oku uqikelelo uphose isiphumo sokugqibela (52-48 Ikhefu) ngamanqaku omyinge ezine.

    1. Sebenzisa isikhokelo impazamo uphando ezichazwe kwesi sahluko zizonke ukuqinisekisa ukuba yeyiphi na ezonakalayo.
    2. impendulo YouGov emva konyulo (https://yougov.co.uk/news/2016/06/24/brexit-follows-close-run-campaign/) wacacisa: "Oku kubonakala kwi inxalenye enkulu ngenxa nabathathe - into besesitshilo lonke iya kuba kakhulu kwisiphumo elugqatsweni nezambatho elungeleleneyo ezinjalo. imodeli yethu kaGrant yayisekelwe, ngokuyinxenye, nokuba abakhe yavotelwa kunyulo jikelele lokugqibela yaye kwinqanaba dululu wangaphezu unyulo jikelele akonwabanga umfuziselo, ingakumbi North. "Ngaba oku ukutshintsha impendulo yakho inxalenye (a)?

  9. [ phakathi , kufuna nokhowudo ] Bhala yokulinganisa ukubonisa nganye iimpazamo umelo kumfanekiso 3.1.

    1. Dala imeko apho okunene ezi iimpazamo ziyahlabana.
    2. Dala imeko apho iimpazamo eqhola omnye komnye.

  10. [ kakhulu kakhulu , kufuna nokhowudo ] Uphando Blumenstock noogxa (2015) ebandakanyeka ekwakheni sokufunda umatshini ungasebenzisa data wokulanda yedijithali ukuqikelela iimpendulo kuphando. Ngoku, uza kuzama into efanayo kunye dataset eyahlukileyo. Kosinski, Stillwell, and Graepel (2013) bafumanisa ukuba Facebook uthanda ulaziyo iimpawu ngamnye kunye neempawu. Okumangalisayo kukuba, ezi zinto zenzeka njani kuba oluchanileyo ngaphezu abahlobo kunye nabalingane (Youyou, Kosinski, and Stillwell 2015) .

    1. Funda Kosinski, Stillwell, and Graepel (2013) , kwaye ngokufanayo Umfanekiso 2. ziyafumaneka iinkcukacha zabo apha: http://mypersonality.org/
    2. Ngoku, phinda Umfanekiso 3.
    3. Okokugqibela, zama imodeli yabo data yakho kwiFacebook eyakho: http://applymagicsauce.com/. kakuhle njani umsebenzi wakho?

  11. [ phakathi ] Toole et al. (2015) iirekhodi ukusetyenziswa umnxeba iinkcukacha (CDRs) ukusuka mobile phones ukuqikelela iintsingiselo ngqesho aggregate.

    1. Bathelekise uyilo Toole et al. (2015) kunye Blumenstock, Cadamuro, and On (2015) .
    2. Ngaba ucinga CDRs kufuneka endaweni iisaveyi zemveli, kuncedisana nabo okanye kusetyenziswa konke konke nkqubo karhulumente ukulandelela ngqesho? Ngoba?
    3. Bubuphi ubungqina ezaziza kuqinisekisa ukuba CDRs kungathatha indawo ngokupheleleyo amanyathelo yemveli izinga lentswela?

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