Activities

Key:

  • selekanyo sa bothata: ho le bonolo ho le bonolo , tse mahareng seaplane , thata ka thata , Thata haholo ka thata
  • ho hloka ea lipalo ( ho hloka ea lipalo )
  • hloka Coding ( hloka Coding )
  • pokello ya data ( pokello ya data )
  • favoritos oa ka ( thatohatsi ea ka )

  1. [ seaplane , thatohatsi ea ka ] Algorithmic tsietsoa e ne e le bothata ba Google Ntaramane Trends. Bala pampiri ke Lazer et al. (2014) , le ho ngola ka karabo e kgutshwanyane, e hlakileng ya imeile ho moenjiniere nakong Google hlalosa bothata le ho fana ka maikutlo a itseng ea kamoo ho ka lokisa bothata.

  2. [ seaplane ] Bollen, Mao, and Zeng (2011) e bolela hore data ho tswa Twitter ka sebelisoa ho bolela esale pele' marakeng Stock. Tse kang ho batla sena se ile sa lebisa ho bōptjoa lekhoakhoa la letlole la ramosebetsi-Derwent Capital Markets-ho sebelise a 'marakeng oa matsete thehiloeng ya data bokella ho tloha Twitter (Jordan 2010) . Ke bopaki bofe bo u ne u tla batla ho bona pele ho beha chelete ea hao ka letlole la seo?

  3. [ ho le bonolo ] Le hoja ba bang ba buellang bophelo bo botle setjhaba sefako e-lisakerete joalokaha ya dithuso e atlehang bakeng sa ho tsuba cessation, ba bang ba lemosa ka likotsi le bokhoni bo kang bo phahameng tseo ba maemo 'bokoali. Nka hore mofuputsi e mong o etsa qeto ea ho ithuta maikutlo a sechaba ka nģ'a e-lisakerete ke bokella e-lisakerete tse amanang Twitter posts by le ho khanna Analysis maikutlo.

    1. ke biases tharo ka etsahala hore u fetisisa tšoenyehile ka thutong ena ke efe?
    2. Clark et al. (2016) matha feela thuto eo. Taba ea pele, ba ile ba bokella 850,000 tweets hore sebelisoa e-sakerete amanang mantswe tsoang January 2012 ho pholletsa December 2014. Ha feta tlhahlobo ka katleho le kamano e haufi, ba ile ba hlokomela hore ba bangata ba tweets tsena li ne li itirisang tsa (khr, eseng hlahisoang ke batho) 'me ba bangata ea tweets tsena itirisang tsa ne hantle lipapatso. Ba ile ba qapa e Human bonoa kgato-tharabololo ya ho arohana tweets gana tsoang tweets manyolo. U sebelisa Human ena lemoha kgato-tharabololo ya ba ile ba fumana hore 80% ea tweets ne ba itirisang tsa. Na lokisitsoe'ng ena fetola karabo ea hao ho ea karolong (a)?
    3. Ha ba bapisa maikutlo a tweets manyolo le gana ba ile ba fumana hore tweets gana ke e ntle haholoanyane ho feta tweets manyolo (6.17 bapisiwa 5.84). Na lokisitsoe'ng ena fetola karabo ea hao ho (b)?

  4. [ ho le bonolo ] Ka November 2009, Twitter fetola potso ka lebokoseng la Tweet tsoang ho "U etsa'ng?" Ho "Ho Etsahala'ng?" (Https://blog.twitter.com/2009/whats-happening).

    1. U nahana hore ho etsoa phetoho ea atindika tla ama ba neng ba Tweet le / kapa hore na ba Tweet?
    2. Bolela e 'ngoe projeke ho etsa lipatlisiso tseo u ka khetha e potlakileng eo "U etsa'ng?" Ba hlalosetse hore na ke hobane'ng.
    3. Bolela e 'ngoe projeke ho etsa lipatlisiso tseo u ka khetha e potlakileng eo "Ho Etsahala'ng?" Hlalosa hore na ke hobane'ng.

  5. [ seaplane ] Kwak et al. (2010) hlahlobisisa Profiles limilione tse 41.7 user want-meet.ru, bilione 1.47 likamano tsa sechaba, taba 4262 Trending lihlooho tse, 'me tweets limilione tse 106 pakeng tsa June 6th le June ka 31st, 2009. E Thehiloe ho Analysis ba utloa sena ba etsa qeto ea hore Twitter sebeletsa eketsehileng e le seaplane e ncha ea boitsebiso bo arolelana ntle le netweke sechabeng.

    1. Nahana ka Kwak et al a li fumana tsela ha bo ea mofuta ofe etsa lipatlisiso ne u tla etsa'ng ka tlhahisoleseding Twitter? Mofuta ofe etsa lipatlisiso ne u sa etse ka tlhahisoleseding Twitter? Hobane'ng?
    2. Ka 2010, Twitter phaella sa Who Ho Latela tšebeletso ea etsa tlhahiso ea hore a lokiselitsoe mekhatlo basebedisi. dikgothaletso tharo bontšoa ka nako leqepheng khōlō. Dikgothaletso ba atisa ho nkiloeng motho a "metsoalle-of-metsoalle," 'me mabitso bobeli ba boetse ba bonahatsa puello eo. Basebedisi ba ka khatholla ho bona sete e ncha ea dikgothaletso kapa etela leqepheng la le lethathamo telele dikgothaletso. Na u nahana hore tšobotsi ee e ncha e ne e tla fetoha karabo ea hao ho ea karolong a)? Ke hobane'ng ha kapa hore na ke hobane'ng ha ho joalo?
    3. Su, Sharma, and Goel (2016) hlahlojoa phello ea Who Ho Latela tšebeletso ea' me ba fumana hore le hoja basebedisi mose ho ratoa manyenyane a rua molemo dikgothaletso, e leng basebedisi ho fetisisa ratoa rue letho haholo ho feta karolelano. Na lokisitsoe'ng ena fetola karabo ea hao ho ea karolong b)? Ke hobane'ng ha kapa hore na ke hobane'ng ha ho joalo?

  6. [ ho le bonolo ] "Retweets" ba atisa ho a sebelisa ho lekanyetsa tšusumetso le jala tšusumetso on Twitter. Qalong, basebedisi ile ka tlameha ho kopitsa u koale ea Tweet ba ratoa Tag mongoli mantlha tsa hae le bana / mohele hae, 'me ka bowena thaepa "RT" pele Tweet ho bontša hore ho e retweet. Joale, ka 2009 Twitter phaella e le "retweet" konopo. Ka June 2016, Twitter entse hore basebedisi ho retweet tweets habo bona (https://twitter.com/twitter/status/742749353689780224). Na u nahana hore liphetoho tsena lokela ama tsela eo u sebelisa "retweets" ka ho etsa lipatlisiso hao? Ke hobane'ng ha kapa hore na ke hobane'ng ha ho joalo?

  7. [ seaplane , pokello ya data , hloka Coding ] Michel et al. (2011) hahoa e polokelo hlahella ho tloha ho bapala ka matla Google ho digitize libuka. Sebelisa phetolelo ea pele ea polokelo, e leng e ile ea hatisoa ka 2009 'me e e-na fetang limilione 5 libuka digitized, baqapi ba hlahlobisisa lentsoe tšebeliso maqhubu ho fuputsa liphetoho puo le mekhoa tsa setso. Haufinyane Google Books Corpus ile ea e-ya data e ratoang mohloli o bakeng bafuputsi, le 2nd phetolelo ea bobolokelo-tshedimosetso e ile ea lokolloa ka 2012.

    Leha ho le joalo, Pechenick, Danforth, and Dodds (2015) o ile a lemosa hore bafuputsi ba lokela ho ka botlalo khethollang ea mohlala tshebetso ya polokelo ea pele e sebelisa bakeng sa etsa liqeto tse sephara. Tsekong ka sehloohong ke hore polokelo e laebraring-joaloka, e nang e 'ngoe ea mong le e mong buka. Ka lebaka leo, motho, mongoli libuka o khona ho bonahala kenya lipoleloana e ncha ka Google Books lokota. Ho feta moo, litemana tse libuka tsa saense etsa e le kabelo ho ntse substantive ea polokelo ea ho pholletsa 1900s eo. Ho phaella moo, ka ho bapisa kamoo liphetolelo tse peli tsa bohlokoa tseo English Tšōmo datasets, Pechenick et al a. fumanoang ka bopaki ba hore ee sa lekanang ya filthara e ne e sebelisetsoa ho hlahisa kgatiso e pele. All ya data e hlokahalang bakeng sa tšebetso e fumaneha here: http://storage.googleapis.com/books/ngrams/books/datasetsv2.html

    1. A Michel et al a. A hatisitsoeng pampiring mantlha (2011) , ba ile ba sebelisa 1st phetolelo ea sete ya data Senyesemane, rera makgetlo a ba tšebeliso ea lilemo tse '1880 "," ka 1912 "le" 1973 ",' me a etsa qeto ea hore" re lebala lintho tse etsahetseng ka potlako ho le fetisetsa selemo le selemo "(sa feiga. 3a, Michel et al a.). Ikatisa morero tšoanang sebelisa 1) 1st phetolelo ea polokelo, a English sete ea datha (jwalo ka sa feiga. 3a, Michel et al a.)
    2. Hona joale ikatisa morero tšoanang le a phetolelong ea 1st, English iqapetsoeng sete ea datha.
    3. Hona joale ikatisa morero tšoanang le a phetolelong ea 2nd ea polokelo, a English sete ea datha.
    4. Qetellong, ikatisa morero tšoanang le a phetolelong ea 2nd, English iqapetsoeng sete ea datha.
    5. Hlalosa ho se tšoane 'me ho tšoana ho teng pakeng tsa merero e mebe tsena tse' nè. Na u lumellana le Michel et al a. A fuoa phetolelo le tlhaloso ea pele ea mokhoa ile ba hlokomela? (Tlhahiso: c) le d) e lokela ho ba le 'ngoe le Figure 16 Pechenick et al a).
    6. Kaha joale le replicated ena lokisitsoe'ng 'ngoe sebelisa fapaneng Google Books corpora, khetha phetoho e' ngoe ea lipuo kapa liketsahalo tsa setso fanoa ka Michel et al a. A hatisitsoeng pampiring ea pele. Na u lumellana le tlhaloso ea bona leseli la mefokolo ea fanoa ka Pechenick et al a.? Ho etsa ho pheha khang ea hao le matla ho, leka ikatisa sa kerafo tšoanang sebelisa liphetolelo tse sa tšoaneng tsa data ya beha joaloka kaholimo.

  8. [ ka thata , pokello ya data , hloka Coding , thatohatsi ea ka ] Penney (2016) hlahloba hore na phatlalatsoa atile hoo e ka bang NSA / porisima e leihlo (khr, e Snowden litšenolo) ka June 2013 le amahanngoa le ea fokotseha bohale 'me ka tšohanyetso a sephethephethe pele ke Wikipedia lihlooho tse buang ka lihlooho eo phahamisa dingongoreho a ba sephiring. Haeba ho joalo, phetoho ena boitšoarong ne e tla ba tsela e lumellanang le le phello e chilling bakiloeng ke boima leihlo. The atamela. Penney (2016) e ka linako tse ling bitsoa ho sitisa nako letoto la lihlooho tse rala le ho e amanang le atamela mathata tse khaolong ka approximating liteko tsoang ya data observational (Karolo 2.4.3).

    Ho khetha sehlooho mantswe, Penney a bua ka ho etsa lenane la sebelisoa ke Lefapha la Homeland Security bakeng Tracking le tlhokomelo metswedi ya dikgang. Siyo lenaneng DHS categorizes dipehelo tse itseng fuputso ho kena mefuta e fapaneng ya ditaba, ke hore, "Bophelo Amehileng," "Infrastructure Security," le "Bokhukhuni." Ka lebaka la sehlopha se ithuta, Penney sebelisa mantswe a mashome a mane e robeli related to "Bokhukhuni" (sheba Lethathamo 8 sehlomathiso). A ntan'o kopanya palokakaretso Wikipedia sehlooho se pono e lokisa mathata ao ka thōko khoeli le khoeli bakeng sa ho ngollana mashome a mane e robeli Wikipedia lihloohong ka nako mashome a mararo-a mabeli a etsang khoeli, ho tloha qalong ea January 2012 ho fihlela qetellong ea August 2014. E le ho matlafatsa ho pheha khang ea hae, o ile a boela a bōpa papiso 'maloa lihlopha tse ka Tracking talimang lintho sehlooho se buang ka lihlooho tse ling.

    Hona joale, u eang ho ikatisa le lelefatsa Penney (2016) . ya data All tala hore u tla hlokang bakeng sa mosebetsi ona e fumaneha ho tloha Wikipedia (https://dumps.wikimedia.org/other/pagecounts-raw/). Kapa o ka e fumana ho tloha R sephutheloana wikipediatrend (Meissner and Team 2016) . Ha u ngola-up likarabo tsa hao, ka kōpo hlokomela tseo e leng mohloli o ya data o sebelisoa. (Hlokomela: Mosebetsi ona tšoanang boetse le hlaha Khaolong ea 6)

    1. Bala Penney (2016) le ho ikatisa Figure 2 e leng bontša talimang lintho leqephe for "Bokhukhuni" leqepheng la -related pele le ka mor'a Snowden tšenolo. Hlalosa se fumaneng eo.
    2. Ka mor'a moo, ikatisa feiga 4a, e leng bapisa sehlopha se ithuta ( "Bokhukhuni" -related lihloohong) le sehlopha se comparator sebelisa mantswe hlotjhwa ka mekgahlelo tlas'a "DHS & Other mekhatlo" ho tswa lenaneng la DHS (sheba Sehlomathiso Lethathamo 10). Hlalosa se fumaneng eo.
    3. A karolong e b) U tšoantša sehlopha se ithuta e le hore sehlopha se le seng comparator. Penney boetse bapisoa le lihlopha tse ling tse peli comparator: "Infrastructure Security" -related lihloohong (Sehlomathiso Lethathamo 11) le e ratoang maqephe Wikipedia (Sehlomathiso Lethathamo 12). Nyolohela nang le mefuta e meng ea comparator sehlopha sena, 'a leke ha lintho tse epolotsoeng ho tloha karolong e b) e ela hloko kgetho ya hao ya comparator sehlopha. E leng qeto e thehiloeng tsebong ea comparator sehlopha se utloahala ka ho fetisisa? Hobane'ng?
    4. mongoli o ile a re mantswe amanang "Bokhukhuni" li ne li sebelisoa ho khetha lihlooho tse Wikipedia hobane muso oa United States bontšitsoeng bokhukhuni e le tokafatso konopo bakeng litloaelo tsa bona Inthaneteng leihlo. Joalokaha cheke ea tsena 48 "Bokhukhuni" mantswe -related, Penney (2016) boetse khanna phuputso e entsoeng mabapi le MTurk botsa arabetseng ho nkang mong le e mong oa mantswe ya ka dipehelo tsa Mathata Government, Privacy-nahanela, le qoba (Sehlomathiso Lethathamo 7 le ea 8). Ikatisa phuputsong hodima MTurk le bapisa diphetho tsa hao.
    5. Thehiloe fella ka karolo d) le ho bala ya hao ya sehlooho se reng, na u lumellana le qeto e thehiloeng tsebong ea ka mongoli oa sehlooho mantswe a sebelisana le sehlopha ithuta? Ke hobane'ng ha kapa hore na ke hobane'ng ha ho joalo? Haeba ha ho joalo, u ne u fana ka maikutlo a e-na le?

  9. [ ho le bonolo ] Efrati (2016) litlaleho, thehiloe tlhahisoleseding e lekunutu, e le hore "palo yohle kopanela boboleling" on Facebook ne a hana ho latela selemo mabapi ya 5.5% fetang selemo hanyenyane "tšimolohong kopanela boboleling hasa" e ne e fatše 21% selemo sa nako e fetang selemo. fokotseha ena e ne e haholo-holo a hlobaetsang le basebedisi Facebook tlas'a lilemo tse 30 bogolo. Tlaleho eo e ngotsoe fokotseha ho lintlha tse peli. E 'ngoe ke ho hlokomela kholo ea palo ea "metsoalle" batho ba on Facebook. E 'ngoe ke hore ba bang ba mosebetsi oa ho abelana lintho e ile a khaotsa ho melaetsa le libapali tse kang SnapChat. Tlaleho eo e boetse e senola maqiti a 'maloa Facebook ba ile ba leka ho boost kopanela boboleling, ho akarelletsa News Feed dikgato-tharabololo tweaks tse etsang hore lintho tse ngotsoeng moo mantlha ipha matla, hammoho le likhopotso tsa periodical tsa mantlha posts by basebedisi "Ka Letsatsi la Ena" lilemo tse' maloa tse fetileng. diphelelo seo, haeba leha e le efe, ha se fumaneng bana ba bakeng sa bafuputsi ba batlang ho sebelisa Facebook e le mohloli ya data?

  10. [ seaplane ] Tumasjan et al. (2010) e ile ea tlaleha hore palo ea tweets bua e mokha oa lipolotiki matched kabelo ya dikgetho hore mokha o ile a fumana ka dikgetho paramente ea Jeremane ka 2009 (Figure 2.9). Ka mantsoe a mang, it bonahala hore o ne a ka sebelisa Twitter ho noha dikgetho. Ka nako eo thuto ea sena e ile ea hatisoa e ne e nkoa e thabisang haholo hobane ho ne ho bonahala ho bontša ho sebelisa bohlokoa bakeng sa e-ba mohloli o tloaelehileng oa ya data e khōlō.

    Fuoa litšobotsi tse mpe tsa data ya khōlō, leha ho le joalo, u lokela ho hang-hang ba lekhonono ea sephetho sena. Majeremane a on Twitter ka 2009 e ne e le haholo bao e seng moemeli sehlopha sena, 'batšehetsi ba motho e mong a ka' na Tweet mabapi lipolotiking khafetsa. Kahoo, ho bonahala eka ho makatse hore ebe biases tsohle ka etsahala hore u ne u ka inahanela ne a ka tsela e itseng hlakola tsoa. Ha e le hantle, liphello e ka Tumasjan et al. (2010) e ile ea e-ba molemo haholo hore ke 'nete. Ka pampiri ea bona, Tumasjan et al. (2010) nkoa a tšeletseng mekga e theha mokhatlo oa lipolotiki: Christian Mademokrate (CDU), Christian Social Mademokrate (CSU), SPD, Liberals (FDP), The Left (Shoa Linke), le Green Party (Grüne). Leha ho le joalo, a boletsweng ka ho fetisisa Jeremane mokha oa lipolotiki on Twitter ka nako eo e neng e le Pirate Party (Piraten), phathing e 'ngoe eo ba loanela molao oa tsamaiso,' muso oa Internet. Ha Mokha oa Pirate ile akarelletsa Analysis, e Twitter bua fetoha polelelopele tšabehang ea liphetho dikgetho (Figure 2.9) (Jungherr, Jürgens, and Schoen 2012) .

    Leka 2,9: Twitter bua hlaha ho noha liphello tsa 2009 dikgetho Jeremane (Tumasjan et al a 2010.), Empa lebaka lena fellang kateng le ho itšetleha ka ba bang hatellang le ahloloe ka leeme khetho ea (Jungherr, Jürgens, 'me Schoen 2012).

    Leka 2,9: Twitter bua hlaha ho noha liphello tsa 2009 dikgetho Jeremane (Tumasjan et al. 2010) , Empa lebaka lena fellang kateng le ho itšetleha ka ba bang hatellang le ahloloe ka leeme khetho ea (Jungherr, Jürgens, and Schoen 2012) .

    Ka mor'a moo, bafuputsi tse ling lefatšeng ka bophara ba sebelisa mekhoa e-joalo fancier a sebelisa Analysis maikutlo ho khetholla pakeng tsa ntle 'me a fosahetseng bua ba mekga-e le hore ho ntlafatsa bokhoni ba ya data Twitter ho noha mefuta e fapaneng ya mefuta e fapaneng ya likhethong (Gayo-Avello 2013; Jungherr 2015, Ch. 7.) . Mona 's kamoo Huberty (2015) akaretsa liphello tsa boiteko ba tsena ho noha likhethong:

    "Bohle tsejoa bonelang mekgwa thehiloeng metswedi ya dikgang ba hlōlehile ha tlas'a likhatello tsa 'nete bonelang dikgetho ea pele-sheba. ho hloleha ha tsena bonahalang eka ke ka lebaka la ho thepa ea motheo ea metswedi ya dikgang, ho e-na le ho mathata methodological kapa algorithmic. Ka bokhutšoanyane, metswedi ya dikgang sa etse joalo, 'me mohlomong kahobane ha ho mohla e tla, u nyehele e tsitsitseng, e unbiased, moemeli setšoantšo sa electorate eo; 'me bebofalletsa disampole ea metswedi ya dikgang ka hloka ya data e lekaneng ea ho lokisa mathata ana ngolang hoc. "

    Bala ka tse ling tsa ho etsa lipatlisiso tseo lebisa Huberty (2015) ho etsa qeto eo, 'me ngola leqepheng la' ngoe memo botjha ho nkgetheng theha mokhatlo oa lipolotiki e hlalosang ha le kamoo Twitter lokela ho sebelisoa ho se profetang ea labella likhetho.

  11. [ seaplane ] Ke phapang pakeng tsa kahisano le rahistori e Eng? Ho latela Goldthorpe (1991) , phapang ka sehloohong pakeng tsa kahisano le rahistori ke laola pokello ya data. Bo-rahistori ba ba tlameha ho e sebelisa liemahale li eloa athe setsebi sa kahisano ka serōki pokello bona ya data ho sebelisetsoa merero e tobileng. Bala Goldthorpe (1991) . How e phapang pakeng tsa kahisano le histori e amanang le khopolo ea Custommades le Readymades?

  12. [ ka thata ] Ho Haha ka potso kgale, Goldthorpe (1991) e ile maloa a arabelang tlhoko tse joalo tse mahlonoko tseo, ho kopanyelletsa le e mong ho tloha Nicky Hart (1994) hore a phephetsa boinehelo Goldthorpe ho serōki ya data entse. Ho hlakisa likhaello ba ya data serōki entsoeng, Hart hlalosa ruileng Mosebeletsi Project, phuputso e entsoeng khōlō ho lekanya kamano e pakeng tsa sehlopha sa phedisano le ho vouta e neng e khannoa ke Goldthorpe le basebetsi-'moho ka bohareng ba bo-ya 1960. E le e mong a ka 'na ka lebella hore ho tswa ho setsebi se ea hauhetsoeng etselitsoe ya data tse fetang ya data fumanoa, tsa ba ruileng ba Mosebeletsi Project bokella ya data e neng e lumellanang ho rarolla khopolo sa tsoa sisintsweng ka bokamoso ba sehlopha sa mathata a kahisano a nakong ea eketseha litekanyetso tsa phelang. Empa, Goldthorpe le basebetsi-'moho ka tsela e itseng "lebala" ho bokella boitsebiso bo mabapi le ho vouta boitšoaro ba basali. Mona 's kamoo Nicky Hart (1994) kakareso e lego ka ea ketsahalo kaofela:

    ". . . e [ke] thata ho qoba qeto ea hore basali ba ne ba lea ka la boleloa hobane sena 'serōki entsoeng' sete ea datha ile koalloa ke tlhalohanyo paradigmatic e leng thoko boiphihlelo ba batšehali. Khannoang ke pono mogopolofela tsa sehlopha ka ilibana 'me ae etsa ha e preoccupations motona. . . , Goldthorpe le metsoalle ea hae e hahoa sete ya bopaki bofe bo bonahetseng e leng fepa le hōlisa likhopolong tsa habo bona mogopolofela e-na le ho pepesa bona ho teko le utloahalang la ea adequacy. "

    Hart a tsoela pele:

    "The se fumaneng bonahetseng ea ruileng Mosebeletsi Project re bolella ho eketsehileng ka melemo masculinist oa bohareng ba bo-lilemo tse lekholo kahisano ho feta kamoo ba tsebisa dithulaganyo tsa go stratification, lipolotiki le bophelo tse bonahalang."

    Na u ka nahana ka mehlala e tse ling moo li bokeletseng serōki entsoeng ya data na le biases tsa mokelli ya data hahiloeng ka ho sona? Hona see se bapisa ho tsietsoa algorithmic? Seo diphelelo se ka ba le ha bafuputsi ba lokela ho sebelisa Readymades 'me ha ba lokela ho sebedisa Custommades?

  13. [ seaplane ] Khaolong ena, ke bapisa ya data bokella ka bafuputsi bakeng sa bafuputsi le direkoto tsa la tsamaiso bōpiloe ke dikhamphani le mebuso. Batho ba bang ba bitsa direkoto tsa tsena tsa tsamaiso tsa "tse fumanoang boitsebiso," eo ba lumelang fapane le "data ya entsoe." Ke 'nete hore direkoto tsa la tsamaiso fumanoa ke bafuputsi, empa ba ile ba ba boetse e tlotloang entsoe. Ka mohlala, lik'hamphani tse sa morao-rao tsa theknoloji ba qeta nako e ngata haholo le chelete ba bokella le ho curate ya data bona. Kahoo, litlaleho tsena tsa tsamaiso tsa ba ka bobeli fumanoe 'me etselitsoe, e mpa feela e itšetlehile ka pono ea hao (Figure 2.10).

    Figure 2,10: Setšoantšo se ka bobeli a letata le e mmutla; seo u se bonang itšetlehile ka pono ea hao. Muso le bahoebi direkoto tsa la tsamaiso di ka bobeli fumanoe 'me etselitsoe; seo u se bonang itšetlehile ka pono ea hao. Ka mohlala, direkoto pitso ya data bokella ka khampani selefouno li fumanoa ya data ho tswa lehlakoreng la ea etsa. Empa, tsena e tobileng direkoto tsa tšoanang li etselitsoe ya data pono ea motho e mong ho sebetsa mo lefapheng la tshupomolato oa k'hamphani fono. Source: Wikimedia Commons

    Figure 2,10: Setšoantšo se ka bobeli a letata le e mmutla; seo u se bonang itšetlehile ka pono ea hao. Muso le bahoebi direkoto tsa la tsamaiso di ka bobeli fumanoe 'me etselitsoe; seo u se bonang itšetlehile ka pono ea hao. Ka mohlala, direkoto pitso ya data bokella ka khampani selefouno li fumanoa ya data ho tswa lehlakoreng la ea etsa. Empa, tsena e tobileng direkoto tsa tšoanang li etselitsoe ya data pono ea motho e mong ho sebetsa mo lefapheng la tshupomolato oa k'hamphani fono. Source: Wikimedia Commons

    Fana ka mohlala oa mohloli o ya data moo ho bona ka bobeli e fumanoang le etselitsoe ho molemo ha ba sebelisa hore mohloli o moholo data ya ho etsa lipatlisiso.

  14. [ ho le bonolo ] Ka moqoqo nahannoeng, Christian Sandvig le Eszter Hargittai (2015) e hlalosa mefuta e 'meli ea ho etsa lipatlisiso tsa digital, moo tsamaiso dijethale ke "seletsa" kapa "ntho e mo khannele thuto." Mohlala oa mofuta oa pele oa ho ithuta o hokae Bengtsson le basebetsi-'moho (2011) sebelisoa ya data fono cellular ho Track ho falla ka mor'a hore tšisinyeho ea lefatše Haiti ka 2010. mohlala oa mofuta ofe ea bobeli ke hona moo Jensen (2007) lithuto tsa ka moo thehiloeng lithelefono tsa cellular ho pholletsa Kerala, India mbano ya mabe na ea ka tšebetso ea 'marakeng kaha litlhapi. Nka fumana sena thusa hobane e clarifies hore lithuto tsa sebelisa dijethale ya data mehloling ka ba le lipakane tse fapaneng haholo esita le haeba ba ba sebelisa mofuta o tšoanang oa ho tsoe mohloling ya data. E le hore ho hlakisa ka ho eketsehileng phapang ena, e hlalosa lithuto tsa 'nè tseo u nile ka bone:' meli tse sebelisang tsamaiso dijethale joalokaha seletsa sa le tse peli tse a sebelisa tsamaiso dijethale joalokaha ntho e mo khannele thuto. U ka sebelisa mehlala khaolo ena haeba u batla.

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