eme

Key:

• ogo ike: mfe , na-ajụ , ike , Nnọọ ike
• -achọ ná mgbakọ na mwepụ ( )
• -achọ nzuzo ( )
• data collection ( )
• m ọkacha mmasị ( )

1. [ , ] Algorithmic etinye dị nsogbu Google Flu Trends. -Agụ akwụkwọ akụkọ ahụ site Lazer et al. (2014) , ma na-ede dị mkpirikpi, doro anya email na engineer na Google na-akọwa nsogbu ahụ na àjà ihe echiche nke otú idozi nsogbu.

2. [ ] Bollen, Mao, and Zeng (2011) na-ekwu na data site na Twitter ike ga-eji ịkọ ngwaahịa ahịa. Nke a Inweta mere ka e nke a oke ego-Derwent Capital Markets-itinye ego na ngwaahịa ahịa dabeere na data anakọtara site na Twitter (Jordan 2010) . Ihe àmà na-egosi ga na ị chọrọ ịhụ tupu ya etinye ego gị na na enweta ego?

3. [ ] Ezie na ụfọdụ ike ọha akwado ọṅụ n'eto e-siga dị ka ihe irè enyemaka n'ihi na ise siga cessation, ndị ọzọ ná ntị banyere ihe ndị pụrụ ize ndụ, dị ka elu-etoju nke nicotine. Were ya na a na-eme nchọpụta kpebie na-amụ echiche ọha na eze n'ebe e-sịga site obon e-sịga metụtara Twitter posts na-eduzi mmetụta analysis.

   1. Gịnị bụ atọ na o kwere omume biases na ị bụ ọtụtụ nchegbu banyere ke ibuotikọ emi?
   2. Clark et al. (2016) ahụ dị nnọọ ọmụmụ ihe ahụ. Mbụ, ha chịkọtara 850,000 tweet na-eji e-siga na-metụtara Keywords si January 2012 site December 2014. Mgbe ha lerukwuru ya anya, ha chọpụtara na ọtụtụ n'ime ndị a tweet e akpaghị aka (ie, adịghị emepụta ụmụ mmadụ) na ọtụtụ n'ime ndị a akpaghị aka tweet ndị nnoo mkpọsa ngwá ahịa. Ha mepụtara a Human Detection algọridim ikewapụ akpaghị aka tweet si organic tweet. Na iji Human Ịchọpụta na algọridim ha chọpụtara na 80% nke tweet e akpaghị aka. Ndi emi Inweta ịgbanwe gị azịza akụkụ (a)?
   3. Mgbe ha tụnyere ndị mmetụta na organic na akpaghị aka tweet ha chọpụtara na akpaghị aka tweet bụ ka mma karịa organic tweet (6.17 vesos 5.84). Ndi emi Inweta ịgbanwe gị azịza (b)?

4. [ ] Na November 2009, Twitter gbanwere ajụjụ na tweet igbe si "Gịnị ka ị na-eme?" Ka "Gịnị na-eme?" (Https://blog.twitter.com/2009/whats-happening).

   1. Olee otú i chere mgbanwe nke kpaliri ga-emetụta onye tweet na / ma ọ bụ ihe ha tweet?
   2. Aha otu nnyocha nke ị ga-ahọrọ ndị ozugbo "Gịnị ka ị na-eme?" Kọwaa ihe mere.
   3. Aha otu nnyocha nke ị ga-ahọrọ ndị ozugbo "Gịnị na-eme?" Kọwaa ihe mere.

5. [ ] Kwak et al. (2010) nyochara na-egosi 41.7 nde onye ọrụ profaịlụ, 1.47 ijeri na-elekọta mmadụ na ibe ya, 4262 Trending isiokwu, na 106 nde tweet n'etiti June 6 na June 31st, 2009. Dabere na nke a analysis ha kwubiri na Twitter na-eje ozi ọzọ dị ka a ọhụrụ ọkara nke ọmụma na-ekere òkè karịa a elekọta mmadụ na netwọk.

   1. Ịtụle Kwak et al si Inweta, ihe ụdị nnyocha ị ga-eme na Twitter data? Olee ụdị nnyocha bụ na ị gaghị eme ya na Twitter data? N'ihi gịnị?
   2. Na 2010, Twitter kwukwara a Ònye Iji Soro ọrụ na-eme ka ahaziri aro ka ndị ọrụ. Atọ atụ aro na-egosi na oge na isi na peeji nke. Aro na-emekarị sii onye "enyi nke na-enyi," na nkwanyerịta kọntaktị na-na-egosipụta na nkwanye. Ọrụ nwere ike nwee ume ịhụ ọhụrụ set nke na-atụ aro ma ọ bụ gaa a na peeji nke na a aba ndepụta nke na-atụ aro. Ị na-eche nke a ọhụrụ mma ga-agbanwe gị azịza akụkụ a)? Gịnị mere ma ọ bụ gịnị mere?
   3. Su, Sharma, and Goel (2016) inyocha mmetụta nke Ònye Iji Soro ọrụ na chọpụtara na mgbe ọrụ gafee ewu ewu ụdịdị dị iche iche uru site na-atụ aro, ndị kasị ewu ewu ọrụ uru n'ụzọ ihe karịrị nkezi. Ndi emi Inweta ịgbanwe gị azịza akụkụ b)? Gịnị mere ma ọ bụ gịnị mere?

6. [ ] "Retweets" na-eji tụọ mmetụta na-agbasa nke mmetụta na Twitter. Ná mmalite, ndị ọrụ nwere na-idetuo na mado na tweet na ha mmasị, ịkpado mbụ na-ede akwụkwọ na ya / ya ahụ, na-aka pịnye "RT" tupu tweet na-egosi na ọ bụ a retweet. Mgbe ahụ, na 2009 Twitter kwukwara a "retweet" button. Na June 2016, Twitter mere ka ndị ọrụ na-retweet ha tweet (https://twitter.com/twitter/status/742749353689780224). Ị na-eche mgbanwe ndị a kwesịrị isi metụta otú i si eji "retweets" gị nnyocha? Gịnị mere ma ọ bụ gịnị mere?

7. [ , , ] Michel et al. (2011) wuru a corpus abụrụ si Google si mgbalị digitize akwụkwọ. Iji mbụ version nke corpus, nke e bipụtara na 2009 na e dere n'elu 5 nde digitized akwụkwọ, ndị dere nyochaa okwu ojiji ugboro ole na ichoputa asụsụ mgbanwe na omenala na ọnọdụ. N'oge na-adịghị Google Books Corpus ghọrọ a na-ewu ewu data isi iyi n'ihi na-eme nnyocha, na a 2nd version nke nchekwa data e wepụtara na 2012.

   Otú ọ dị, Pechenick, Danforth, and Dodds (2015) aka ná ntị na-eme nnyocha mkpa n'ụzọ zuru ezu mara na ụfọdụ usoro nke corpus tupu eji ya maka na-eru sara mbara nchikota. Isi okwu a bụ nke na corpus bụ akwụkwọ ndị dị ka, nwere otu n'ime akwụkwọ nke ọ bụla. N'ihi ya, otu onye, ​​ọtụtụ na-ede akwụkwọ bụ ike otú ahụ fanye ọhụrụ nkebi ahịrịokwu n'ime Google Akwụkwọ ọkọwa okwu. Ọzọkwa, ndị ọkà mmụta sayensị odide ịbụ ihe na-esiwanye substantive òkè nke corpus ofụri 1900s. Ke adianade do, site atụnyere abụọ nsụgharị nke English Ụgha datasets, Pechenick et al. hụrụ na-egosi na ezughi oke nzacha na-eji na-amị akpa version. All nke data dị mkpa maka ọrụ bụ dị ebe a: http://storage.googleapis.com/books/ngrams/books/datasetsv2.html

   1. Na Michel et al. Mbụ akwụkwọ (2011) , ha na-eji 1st version nke English data set, kpara nkata ugboro nke ojiji nke afọ "1880", "1912" na "1973", wee kwuo na "anyị bụ -echefu anyị n'oge gara aga ngwa ngwa afọ na-agafe "(Fig. 3A, Michel et al.). Emepụtaghachi otu ibé iji 1) 1st version nke corpus, English dataset (otu ihe Fig. 3A, Michel et al.)
   2. Ugbu a emepụtaghachi otu ibé na 1st version, English akụkọ ifo dataset.
   3. Ugbu a emepụtaghachi otu ibé na 2nd version nke corpus, English dataset.
   4. N'ikpeazụ, emepụtaghachi otu ibé na 2nd version, English akụkọ ifo dataset.
   5. Kọwaa ọdịiche yie anọ ndị a plots. Ì kwetara ihe Michel et al. Mbụ nkọwa nke hụrụ emekarị? (Ndumodu: c) ma d) ga-abụ otu dị ka Ọgụgụ 16 na Pechenick et al.)
   6. Ugbu a na ị replicated a onye na-achọta iji dị iche iche Google Books corpora, họrọ ọzọ asụsụ mgbanwe ma ọ bụ omenala phenomena adade ke Michel et al. Mbụ akwụkwọ. Ì kwetara ihe ha akukọ-isi na ìhè nke na-agaghị emeli adade ke Pechenick et al.? Iji mee ka gị sere okwu ike, na-agbalị emepụtaghachi otu eserese site na iji iche iche na nsụgharị nke data setịpụrụ dị n'elu.

8. [ , , , ] Penney (2016) explores ma zuru ebe nile bu ihe NSA / prism surveillance (ie, onye Snowden mkpughe) na June 2013 jikọtara a nkọ na mberede ọnụ ke okporo ụzọ Wikipedia isiokwu na isiokwu na-ewu nzuzo nchegbu. Ọ bụrụ otú ahụ, mgbanwe a na omume ga-agbanwe agbanwe na a chilling mmetụta n'ihi uka onyunyo. The obibia nke Penney (2016) Mgbe ụfọdụ a na-akpọ onye na kwụsị oge usoro imewe na na-metụtara ndị na-eru nso ke ibuot banyere approximating nwere si observational data (Nkebi 2.4.3).

   Ịhọrọ isiokwu Keywords, Penney kwuru na ndepụta na-eji US Ngalaba n'ala nna Nche n'ihi na nsuso na nlekota mmadụ mgbasa ozi. The DHS ndepụta categorizes ụfọdụ na ọchụchọ n'ime a nso nke nsogbu, ie "Health Concern," "Infrastructure Security," na "Iyi ọha egwu." N'ihi na ìgwè ọmụmụ, Penney eji na iri anọ na asatọ Keywords metụtara "Iyi ọha egwu" (lee Isiokwu 8 Odide Ntụkwasị). Ọ mgbe ahụ aggregated Wikipedia isiokwu echiche adabere na kwa ọnwa ihe ndabere maka kwekọrọ ekwekọ iri anọ na asatọ Wikipedia isiokwu karịrị otu iri atọ na abụọ ọnwa oge, site ná mmalite nke January 2012 na njedebe nke August 2014. Iji ike ya sere okwu, ọ na-kere ọtụtụ tụnyere iche iche site nsuso isiokwu echiche na ndị ọzọ isiokwu.

   Ugbu a, ị na-aga emepụtaghachi na ịgbatị Penney (2016) . All ọnyá ọhụrụ data na ị ga-mkpa maka ọrụ a dị site na Wikipedia (https://dumps.wikimedia.org/other/pagecounts-raw/). Ma ọ bụ i nwere ike inwe ya site na R ngwugwu wikipediatrend (Meissner and Team 2016) . Mgbe ị dee-elu gị na-azaghachi, biko mara nke data isi iyi na ị na-eji. (Note: Otu ọrụ dịkwa ná Chapter 6)

   1. -Agụ Penney (2016) na emepụtaghachi ọgụgụ 2 nke na-egosi na peeji nke echiche maka "Iyi ọha egwu" -related peeji tupu mgbe Snowden echiche. Ịkọwa Nchoputa.
   2. Next, emepụtaghachi Fig 4A, nke na-eji tụnyere ndị ìgwè ọmụmụ ( "Iyi ọha egwu" -related isiokwu) na a comparator otu eji Keywords categorized n'okpuru "DHS & ndị ọzọ Ụlọ ọrụ" si DHS ndepụta (Lee nkowa Isiokwu 10). Ịkọwa Nchoputa.
   3. Na akụkụ b) ị tụnyere ndị ìgwè ọmụmụ na otu comparator otu. Penney nwekwara tụnyere abụọ ọzọ comparator iche iche: "Infrastructure Security" -related isiokwu (Odide Ntụkwasị Isiokwu 11) na-ewu ewu Wikipedia peeji nke (Odide Ntụkwasị Isiokwu 12). Gbagote na onye ọzọ comparator otu, ma nwalee ma ọ bụrụ na Nchoputa si akụkụ b) bụ mwute na ị na-ahọrọ comparator otu. Nke oke nke comparator otu anam kasị uche? N'ihi gịnị?
   4. Na-ede kwuru na Keywords ọzọ ha na "Iyi ọha egwu" e ji họrọ Wikipedia isiokwu n'ihi na nke ochichi US e zoro aka na iyi ọha egwu dị ka a isi ziri ezi n'ihi na ya online surveillance omume. Dị ka a ego ndị a 48 "Iyi ọha egwu" -related Keywords, Penney (2016) na-ekenịmde a nnyocha e mere na MTurk arịọ zaghachirinụ na dịruru ọ bụla nke Keywords na okwu nke Government Nsogbu, Privacy-Mmetuta, na izere (Odide Ntụkwasị Isiokwu 7 na nke 8). Emepụtaghachi nnyocha e mere na MTurk na tụnyere gị pụta.
   5. Dabere na ya pụta na akụkụ d) na ị gụọ isiokwu, ị na-ekweta na onye dere ya dere oke nke isiokwu Keywords na ìgwè ọmụmụ? Gịnị mere ma ọ bụ gịnị mere? Ọ bụrụ na ọ bụghị, olee ihe ị ga-atụ aro kama?

9. [ ] Efrati (2016) na-akọ, dabere na nzuzo ozi, na "ngụkọta nkekọrịta" on Facebook ama jụrụ site banyere 5.5% afọ, ihe karịrị afọ mgbe "mbụ na agbasa ozi n'ikuku nkekọrịta" bụ ala 21% afọ, ihe karịrị afọ. Nke a ojuju karịsịa nnukwu na Facebook ọrụ na-erughi afọ 30. The akụkọ ekewet ojuju na abụọ ihe. Otu bụ Mmụba nke ọnụ ọgụgụ nke ndị "enyi" ndị nwere on Facebook. Nke ọzọ bụ na ụfọdụ nkekọrịta ọrụ gbanwere ka izi ozi na-aka dị ka Snapchat. The akụkọ ka anyị mata ọtụtụ ụzọ aghụghọ ndị Facebook gbalịrị mbo mbuli nkekọrịta, gụnyere News Feed algọridim Tweaks na-eme ka mbụ posts ọzọ a ma ama, nakwa dị ka n'oge bụ ihe ncheta nke mbụ posts ọrụ "On a Day" ọtụtụ afọ gara aga. Ihe pụtara, ọ bụrụ na ihe ọ bụla, ọ nchọpụta ndị a nwere maka nnyocha chọrọ iji Facebook dị ka a data isi iyi?

10. [ ] Tumasjan et al. (2010) kọrọ na nkezi nke tweet banyere òtù ndọrọ ndọrọ ekwekọghị nkezi nke votes na party natara na German Omeiwu ntuli aka a na 2009 (ọgụgụ 2.9). Ndị ọzọ okwu, ọ dị ka ị pụrụ iji Twitter ikwu ihe ga-nhoputa ndi ochichi. N'oge ahụ a na-amụ na-ebipụta na e weere ya nnọọ akpali akpali n'ihi na o yiri ka ọ na-atụ aro a bara uru ojiji maka na-ebutekarị nke nnukwu data.

    Nyere ọjọọ atụmatụ nke nnukwu data, Otú ọ dị, ị kwesịrị ị na ozugbo obi abụọ nke a n'ihi. Germany on Twitter na 2009 nwere nnọọ a na-abụghị ndị nnọchiteanya otu, na-akwado nke onye ọzọ nwere ike tweet banyere ndọrọ ndọrọ ọchịchị ọzọ mgbe. N'ihi ya, o yiri ihe ijuanya na niile kwere omume biases na ị nwere ike iche ga-enyetụrụ hichapụ. N'eziokwu, na ya pụta na Tumasjan et al. (2010) mesịrị bụrụ kwa mma na-ezi. Ha akwụkwọ, Tumasjan et al. (2010) atụle isii ndọrọ ndọrọ ọchịchị ọzọ: Christian Democrats (CDU), Christian Social Democrats (CSU), SPD, Liberals (FDP), The Left (Die Linke), na Green Party (Grüne). Otú ọ dị, ihe ndị kasị kwuru German òtù ndọrọ ndọrọ on Twitter n'oge ahụ bụ Paireti Party (Piraten), a party na-akpata ịlụ ọgụ gọọmenti nke Internet. Mgbe Paireti Party e esịne ke analysis, Twitter kwuru na-aghọ a egwu predictor nke ntuli aka pụta (ọgụgụ 2.9) (Jungherr, Jürgens, and Schoen 2012) .

    

    Chepụta 2.9: Twitter kwuru na-egosi ịkọ pụta nke 2009 German ochichi (Tumasjan et al. 2010) , ma nke a n'ihi amama adabere na ụfọdụ aka ike na-enweghị ihe kpatara nhọrọ (Jungherr, Jürgens, and Schoen 2012) .

    Mgbe nke ahụ gasịrị, ndị ọzọ na-eme nnyocha gburugburu ụwa ji fancier ụzọ-dị ka site na iji mmetụta analysis ịmata ọdịiche dị n'etiti nti na-adịghị mma kwuru nke ọzọ-iji melite ike nke Twitter data ịkọ a dịgasị iche iche nke dị iche iche nke ntuli aka (Gayo-Avello 2013; Jungherr 2015, Ch. 7.) . Nke a bụ otú Huberty (2015) kọwaa ihe ha na-arụpụta n'ime ndị a mgbalị ịkọ ntuli aka:

    "All mara ịkọ ụzọ dabeere na mmadụ mgbasa ozi nwere okpu mgbe ọchịchị na-achọ n'aka ezi-atụ-na-achọ electoral ịkọ. Ndị a ọdịda egosi ịbụ n'ihi isi Njirimara nke mmadụ mgbasa ozi, kama ka methodological ma ọ bụ algorithmic isi ike. Na nkenke, na-elekọta mmadụ media-eme adịghị, na eleghị anya, mgbe a ga, na-enye a ufọk ufene, ebinyeghị akụkụ ọ bụla, nnọchiteanya na foto nke onu; na mma samples nke mmadụ mgbasa ozi na-enweghị zuru ezu data idozi nsogbu ndị a biputere hoc. "

    -Agụ ụfọdụ ndị nnyocha na-eduga Huberty (2015) ka ha kwuo ya, na-ede a otu page memo ka a na ndọrọ ndọrọ ọchịchị nwa akwukwo akọwa ma ọ bụrụ na otú Twitter ga-eji na-Eburu amuma ntuli aka.

11. [ ] Gịnị bụ ihe dị iche n'etiti ọkà ná mmekọrịta na a ọkọ akụkọ ihe mere? Dị ka Goldthorpe (1991) , isi ihe dị iche n'etiti ọkà ná mmekọrịta na a ọkọ akụkọ ihe mere bụ achịkwa data collection. Historians na-amanye iji onwunwe ebe sociologists nwere ike ịkwa akwa ha data collection aka kpọmkwem nzube. -Agụ Goldthorpe (1991) . Olee otú ihe dị iche n'etiti sociology na akụkọ ihe mere eme metụtara echiche nke Custommades na Readymades?

12. [ ] Iwuli na aga ajụjụ, Goldthorpe (1991) sere a ọnụ ọgụgụ nke dị oké egwu na-azaghachi, gụnyere otu onye si Nicky Hart (1994) na aka Goldthorpe si etinye onwe ịkwa akwa mere data. Dokwuo anya nwere na-agaghị emeli nke ịkwa akwa mere data, Hart kọwara ndị ọgaranya Ọrụ Project, a nnukwu nnyocha e mere tụọ mmekọrịta dị n'etiti mmadụ na klas na ịtụ vootu na e ekenịmde Goldthorpe na ndị ọrụ ibe ke ufọt ufọt 1960. Dị ka onye pụrụ ịtụ anya ya n'aka ọkà mmụta bụ ndị kwadoro e mere data n'elu hụrụ data, ndị ọgaranya Ọrụ Project anakọtara data na e ahaziri iji lebara a na nso nso a chọrọ tiori banyere ọdịnihu nke na-elekọta mmadụ na klas na oge nke na-amụba ndụ na ụkpụrụ. Ma, Goldthorpe na ndị ọrụ ibe n'ụzọ ụfọdụ "chefuru" na-anakọta ozi banyere ịtụ vootu omume nke ndị inyom. Nke a bụ otú Nicky Hart (1994) nchịkọta dum merenụ:

    ". . . ọ [bụ] isi ike izere ikpebi na ndị inyom omitted n'ihi na a 'ịkwa akwa mere' dataset ya bụ nanị site a paradigmatic mgbagha nke ekwe nwaanyị ahụmahụ. Chụpụrụ site a usoro iwu ọhụụ nke klas nsụhọ na edinam dị ka nwoke ọrụ n'aka. . . , Goldthorpe na ibe ya wuru a set nke ahụrụ anya-àmà nke nri na ozuzu umu aka ha n'ọnụ echiche kama ekpughe ha ka a irè ule nke adequacy. "

    Hart aka iso:

    "The ahụrụ anya Nchoputa nke ndị ọgaranya Ọrụ Project-agwa anyị ihe banyere masculinist ụkpụrụ nke ufọt ufọt narị afọ sociology karịa ha agwa ndị Filiks nke stratification, ndọrọ ndọrọ ọchịchị na ihe onwunwe ndụ."

    Ị pụrụ icheta ihe atụ ndị ọzọ ebe ịkwa akwa mere data collection nwere biases nke data mkpoko wuru n'ime ya? Olee otú nke a tụnyere algorithmic etinye? Ihe pụtara nwere ike a nwere maka mgbe na-eme nnyocha kwesịrị iji Readymades na mgbe ha kwesịrị iji Custommades?

13. [ ] N'Isi nke Iri a, m iche data anakọtara site na-eme nnyocha maka nnyocha na administrative ndia kere site na ụlọ ọrụ ndị na ọchịchị. Ụfọdụ ndị na-akpọ ndị a administrative ndia "hụrụ data," nke ha okpụhọde ye "e mere data." Ọ bụ eziokwu na administrative ndia ẹkụt site na-eme nnyocha, ma ha na-ukwuu e mere. Dị ka ihe atụ, n'oge a tech na emefu nnukwu ichekwa oge na ego ha na-anakọta na curate ha data. N'ihi ya, ndị a administrative ndekọ na-ma hụrụ na e mere, ọ dị na-adabere gị n'ọnọdụ (ọgụgụ 2.10).

    

    Ọgụgụ 2,10: The picture bụ ma a ọbọgwụ na a oke bekee; ihe ị na-ahụ na-adabere na gị anya. Government na azụmahịa ndutịm ndekọ na-ma hụrụ na e mere; ihe ị na-ahụ na-adabere na gị anya. Dị ka ihe atụ, oku data ndia anakọtara site a cell ekwentị ụlọ ọrụ na-achọta data si n'ọnọdụ nke a na-eme nchọpụta. Ma, ndị a kpọmkwem otu ihe ndekọ na-e data n'ọnọdụ nke onye na-arụ ọrụ ịgba ụgwọ ngalaba nke ekwentị ụlọ ọrụ. Isi Iyi: Wikimedia Commons

    Bụ ihe atụ nke data iyi ebe ahụ ya ma ka hụrụ na e mere na-enye aka mgbe eji na data isi iyi na-emere nnyocha.

14. [ ] Na a echiche edemede, Christian Sandvig na Eszter Hargittai (2015) na-akọwa abụọ iche iche nke dijitalụ research, ebe digital usoro bụ "ngwá" ma ọ bụ "ihe ọmụmụ." Otu ihe atụ nke mbụ ụdị ọmụmụ na-ebe Bengtsson na ibe (2011) na-eji ekwentị mkpanaaka data soro Mbugharị mgbe ala ọma jijiji na Haiti na 2010. Otu ihe atụ nke abụọ ụdị bụ ebe Jensen (2007) ọmụmụ otú iwebata mobile phones nile Kerala, India impacted ịrụ ọrụ nke ahịa n'ihi na azu. M na-ahụ a na-enye aka n'ihi na ọ na doo anyị anya na ọmụmụ iji dijitalụ data isi mmalite nwere ike inwe nnọọ iche ihe mgbaru ọsọ ọbụna ma ọ bụrụ na ha na-eji otu ụdị data isi iyi. Iji nwetakwuo dokwuo anya a dị iche, na-akọwa anọ ọmụmụ na ị hụrụ: abụọ na-eji a digital usoro dị ka ngwá na abụọ na-eji a digital usoro dị ka ihe ọmụmụ. Ị nwere ike iji ihe atụ si na isiokwu a ma ọ bụrụ na ị chọrọ.