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Algorytm Edge Rank Serwisu Facebook: Narodziny, Rozwój I Działanie W Uj Ęciu Teorii Aktora-Sieci

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Algorytm Edge Rank Serwisu Facebook: Narodziny, Rozwój I Działanie W Uj Ęciu Teorii Aktora-Sieci 71 Michał Pałasz Uniwersytet Jagiello ński w Krakowie Wydział Zarz ądzania i Komunikacji Społecznej Instytut Kultury e-mail: [email protected] Algorytm Edge Rank serwisu Facebook: narodziny, rozwój i działanie w uj ęciu teorii aktora-sieci Abstrakt Artykuł wychodzi od omówienia metodologii badania (teoria aktora- sieci, autoetnografia), a nast ępnie przedstawia rozwój serwisu Facebook w latach 2004-2018 w perspektywie narodzin i przemian algorytmu kształtu- jącego „aktualno ści” ( News Feed ), okre ślone kluczow ą innowacj ą platformy, po czym w konkluzjach syntetyzuje rozpoznane translacje i modus operandi głównego aktora. Tekst powstał na bazie badania przeprowadzonego na po- trzeby wyst ąpienia autora w ramach II Ogólnopolskiej Interdyscyplinarnej Konferencji Naukowej „TechSpo’18: Władza algorytmów?”, zorganizowanej przez Wydział Humanistyczny Akademii Górniczo-Hutniczej w Krakowie (Kraków, 20-21 wrze śnia 2018). Słowa kluczowe: algorytm Edge Rank, Facebook, media społeczno ściowe, News Feed, teoria aktora-sieci, zarz ądzanie mediami. Wst ęp Artykuł prezentuje rezultaty prowadzonej w duchu teorii aktora-sieci (ANT, ang. actor-network theory ) eksploracji przemian serwisu Facebook w latach 2004-2018, w efekcie których powstał i w których bierze aktywny, sprawczy udział algorytm, okre ślany jako Edge Rank , EdgeRank , Ranking bądź po prostu algorytm serwisu Facebook czy te ż algorytm Facebooka. Mil- cz ąco towarzyszy on w momencie pisania tych słów ponad dwóm miliardom użytkowników serwisu, którzy korzystaj ą z niego co najmniej raz w miesi ącu (Facebook Newsroom 2018a), a ponadto, m.in.: • decyduje, które komunikaty w ramach serwisu docieraj ą do których u żyt- kowników, tworz ąc ba ńki informacyjne (por. Pariser 2011), jak Blue Feed, Red Feed ( „Kanał niebieski, kanał czerwony” – je śli nie zaznaczono ina- czej, tłum. MP), odpowiadaj ące „aktualno ściom” (ang. News Feed, ofi- cjalny produkt serwisu, por. Facebook Newsroom 2018b) liberalnych i konserwatywnych jego u żytkowników w USA (The Wall Street Journal 2018), utrudniaj ące weryfikacj ę tzw. fake news (fałszywych wiadomo ści), 72 Algorytm Edge Rank serwisu Facebook: narodziny, rozwój i działanie w uj ęciu teorii aktora-sieci kluczowych aktorów wyborów prezydenckich w USA oraz referendum w sprawie Brexitu w 2016 roku (Gore 2018); • stwarza zakres zarz ądzania mediami społeczno ściowymi przez podmioty reprezentuj ące innych, tworz ąc nowe zawody i bran że (Pałasz 2018); • gwarantuje monetyzacj ę serwisu (przynoszenie przeze ń zysków), przez umo żliwienie dystrybutorom tre ści wykupu reklam w „aktualno ściach” wybranych grup u żytkowników z pomini ęciem wpływu algorytmu, wi ą- żą c jednocze śnie serwis z aferami, jak „ Cambridge Analytica” (por. The Guardian 2018). Badanie jest transdyscyplinarne, wpisuje si ę m.in. w obszary zaintere- sowa ń cyfrowej humanistyki, kulturoznawstwa, medioznawstwa, zarz ądzania humanistycznego w zakresie zarz ądzania mediami i w humanistyczn ą reflek- sj ę na temat algorytmów (por. Kreft 2015, 2019). 1. Metodologia, teoria aktora-sieci, autoetnografia Przedmiotem badania s ą przemiany serwisu Facebook istotne z per- spektywy powstania i przekształce ń kluczowego dla ń i dla aktorów z nim powi ązanych algorytmu. Badanie przeprowadzono w optyce teorii aktora- sieci z wykorzystaniem technik i narz ędzi wła ściwych analizie tekstu i auto- etnografii. Głównym celem badania jest eksploracja i opis powstania oraz prze- mian badanego algorytmu w perspektywie teorii aktora-sieci, identyfikacja zachodz ących w zwi ązku z tym procesów i aktorów odgrywaj ących poszcze- gólne warianty algorytmu oraz ułatwienie zrozumienia istoty działania tego ż. Materiał badawczy (udost ępniany czytelniczkom i czytelnikom w oddziel- nym pliku: bit.ly/materbad, do którego poszczególnych pozycji odnosz ą w cz ęś ci badawczej artykułu liczby umieszczone w nawiasach kwadrato- wych), stanowi historia serwisu Facebook zapo średniczona przez adekwatne i wiarygodne źródła elektroniczne oraz literatura badawcza przedmiotu i orientacji, a tak że wgl ąd autoetnograficzny autora, zawodowo i naukowo zwi ązanego od 2009 roku z zarz ądzaniem mediami społeczno ściowymi, w szczególno ści za ś z wykorzystaniem dla celów marketingowych serwisu Facebook. Problem badawczy obj ął ukazanie (eksploracj ę i opis) wariantów ist- nienia i działania algorytmu serwisu Facebook, jako fluktuuj ącej, niestabilnej sieci heterogenicznych relacji, procesów i aktorów tworz ących go i przeze ń tworzonych, zapo średniczone przez odpowiedni materiał empiryczny i teore- tyczny. Źródeł teorii aktora-sieci, głównej perspektywy badania, nale ży upa- trywa ć w Studiach nad Nauk ą i Technologi ą (STS, ang. Science and Techno- logy Studies ), w szczególno ści w etnografii laboratorium i antropologicznych 73 Michał Pałasz badaniach praktyk laboratoryjnych. Autorami pierwszych publikacji repre- zentatywnych dla ANT s ą Bruno Latour, Michel Callon i John Law (Abri- szewski 2012: 8). W śród polskich badaczy eksploruj ą j ą głównie przedstawi- ciele Toru ńskiej Szkoły Konstruktywizmu, zwłaszcza Krzysztof Abriszewski (2007, 2012), a tak że Barbara Czarniawska (2004; 2010), Katarzyna Bara ń- ska (2013), Aleksandra Kil (2012; 2015) i Michał Pałasz (2018). W bada- niach nad mediami społeczno ściowymi refleksja z u życiem ANT zdarza si ę rzadko, jakkolwiek z tendencj ą rosn ącą (Couldry 2008; Kil 2012; van Dijck 2013; Krieger & Belliger 2014; Spöhrer & Ochsner 2016; Pałasz 2018). Teoria aktora-sieci bada gor ące momenty fluktuacji wi ęzi, maj ące miejsce w toku kontrowersji, prób sił czy negocjacji mi ędzy heterogenicz- nymi aktorami (Latour 1986: 273), w odniesieniu do których, zgodnie z za- sad ą ogólnej symetrii (Latour 1992:159), nie wnosi si ę z góry o ich spraw- czo ści, skutkiem czego w punkcie wyj ścia nie tylko aktorzy ludzcy, ale tak że pozaludzcy maj ą empirycznie rejestrowaln ą sprawczo ść . Wskazywane bywa, że ANT jest raczej metod ą, ni ż teori ą (Abriszewski 2007:116), jako że nie proponuje ona wyja śnie ń, daje natomiast precyzyjne dyrektywy badawcze, z których podstawow ą jest „pod ąż aj za aktorami” (Czarniawska 2004:781; Latour 2005:12), nakłania do radykalnego empiryzmu, unikania zało żeń i koncentracji na opisie tego, w jaki sposób aktorzy graj ą i s ą odgrywani. Warto zaznaczy ć, że za aktora uznaje si ę to, co działa (Abriszewski 2007:116; 2012:74), bez wzgl ędu na intencje (Latour 2005:76), przy czym ka żdy aktor jest pozbawiony esencji – stanowi on rezultat relacji z innymi aktorami (Bi ńczyk 2005). Aktor zatem jednocze śnie jest w sieci, jak i jest sieci ą. Autoetnografia, stosowana w badaniu narz ędziowo, stanowi hybryd ę autobiografii i etnografii (K ępa 2014:82). W ramach tego badania nale ży j ą rozumie ć jako sposób pozyskiwania danych do analizy, niezapo średniczo- nych, otrzymywanych przez badacza od samego siebie, a tak że jako technik ę ułatwiaj ącą m.in. odkrycie, selekcj ę i ocen ę wiarygodno ści źródeł empirycz- nych. Badanie wpisuje si ę w nurt autoetnografii analitycznej uwzgl ędniaj ąc jego przesłanki: pełne uczestnictwo badacza w badanym otoczeniu (1), re- fleksyjno ść analityczną (2), obecno ść Ja badacza w narracji (3), dialog z in- formatorami innymi ni ż Ja badacza (4) i zaanga żowanie w analiz ę teoretycz- ną (5) (Anderson 2014:144, 149), przy czym punkt (5) spełniony jest o tyle, o ile nie narusza dyrektyw ANT (por. Latour 2005:137; Abriszewski 2012:274). W badaniach kultury cyfrowej autoetnografia wykorzystywana jest m.in. w analizach społeczno ści wirtualnych (Jemielniak 2013), wirtual- nych muzeów (Pałasz 2015a) i zarz ądzania mediami społeczno ściowymi (Pa- łasz 2015b). 74 Algorytm Edge Rank serwisu Facebook: narodziny, rozwój i działanie w uj ęciu teorii aktora-sieci 2. Narodziny, rozwój i działanie algorytmu serwisu Facebook Serwis Facebook zało żono w lutym 2004 roku [10]. U jego pocz ąt- ków nie istniały – oczywiste dzi ś, w 2018 roku – mo żliwo ści publikowania wpisów, zdj ęć czy wideo, nie było powiadomie ń, stron, czatu, dynamicznych tablic profilów osobistych, grup, wydarze ń i wreszcie – „aktualno ści” ( News Feed ), ani algorytmu, który miałby je kształtowa ć. U pocz ątków Facebook był statycznym katalogiem profilów osobi- stych, z jednym zdj ęciem (profilowym), notk ą biograficzn ą, list ą i wyszuki- wark ą znajomych, ustawieniami prywatno ści oraz pó źniej zarzucon ą, opcj ą wizualizacji sieci znajomych. Innymi słowy, na początku był (tylko) profil [11; 16; 28; 32]. 2.1. News Feed 1.0 (wrzesie ń 2006 – listopad 2007). „Aktualno ści” bez algorytmu? News Feed , z którym Facebook bywa dzi ś (nie świadomie) uto żsa- miany [18], powstał we wrze śniu 2006 roku [10], po ponad 2,5 roku od uru- chomienia serwisu, w momencie, w którym korzystało ze ń około 9 milionów użytkowników [12]. Osoby, którym przypisuje si ę zasług ę utworzenia go, to: Chris Cox, Andrew "Boz" Bosworth, Ruchi Sanghvi i Kang-Xiang [7]. W tym samy miesi ącu serwis stał si ę dost ępny dla wszystkich ch ętnych do korzystania ze ń u żytkowników [3]. Mi ędzy lutym 2004 roku a wrze śniem 2006 roku zmienił on tak że domen ę z thefacebook.com na facebook.com [ta ostatnia kosztowała 200 000 $, 32], uruchomił dodawanie zdj ęć , pisanie na tablicach znajomych, grupy, umo żliwił korzystanie ze ń za pomoc ą telefonu komórkowego oraz przedstawił pierwsz ą wersj ę Facebook API [10; 11]. Mi ędzy powstaniem serwisu a wdro żeniem usługi News Feed znacznie wi ęc wzrosła liczba jego u żytkowników, pojawiły si ę nowe mo żliwo ści (stacjonar- nie, mobilnie) dodawania ró żnorodnych typów tre ści (wpisy, zdj ęcia)
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