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Data-Realism: Reading and Writing Datafied Text

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Data-Realism : Reading and Writing Datafied Text. / Erslev, Malthe Stavning; Pold, Søren Bro.

In: Electronic Book Review, 2020.

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Erslev MS, Pold SB. Data-Realism: Reading and Writing Datafied Text. Electronic Book Review. 2020. doi: 10.7273/n381-mk15

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@article{42c256f0b4fc46b9874a78f8a8ae02ed,
title = "Data-Realism: Reading and Writing Datafied Text",
abstract = "In this forward-looking and somewhat tentative call for a realism of data - or a data-realism - we chart out three literary experiments all relating to one of the most pressing aspects of the contemporary conditions of writing, namely the role of data-driven support software including machine learning. Questioning how to read the text{\textquoteright}s data - or the data{\textquoteright}s text - we develop our approach in dialogue with three works of e-lit, arguing that these works present three distinct, yet related, ways of engaging with the underlying data-infrastructures of computerized language. Thus, we read these three works of e-lit in order to examine (1) how predictive keyboards change the notion of who is writing (or texting) whom in Erica Scourti{\textquoteright}s THINK YOU KNOW ME; (2) how Google{\textquoteright}s AdWords algorithm creates and manages a linguistic capitalism as investigated by Pip Thornton{\textquoteright}s {poem}.py; and (3) how the style of generative text is becoming both recognizable and re-mixable, forming a machine learning rhetoric, evident twitter user @KeatonPatti{\textquoteright}s viral “Olive Garden Tweet.” Refraining from presenting a closed conclusion, we instead speculate the relevance of our data-realist approach by presenting an e-lit meditation of the concept, taking the form of the latest iteration of The Poetry Machine: “The Oracle from Selphie.”",
keywords = "realism, data aesthetics, Electronic literature",
author = "Erslev, {Malthe Stavning} and Pold, {S{\o}ren Bro}",
year = "2020",
doi = "10.7273/n381-mk15",
language = "English",
journal = "Electronic Book Review",
issn = "1553-1139",
publisher = "Electronic Book Reviews",

}

RIS

TY - JOUR

T1 - Data-Realism

T2 - Reading and Writing Datafied Text

AU - Erslev, Malthe Stavning

AU - Pold, Søren Bro

PY - 2020

Y1 - 2020

N2 - In this forward-looking and somewhat tentative call for a realism of data - or a data-realism - we chart out three literary experiments all relating to one of the most pressing aspects of the contemporary conditions of writing, namely the role of data-driven support software including machine learning. Questioning how to read the text’s data - or the data’s text - we develop our approach in dialogue with three works of e-lit, arguing that these works present three distinct, yet related, ways of engaging with the underlying data-infrastructures of computerized language. Thus, we read these three works of e-lit in order to examine (1) how predictive keyboards change the notion of who is writing (or texting) whom in Erica Scourti’s THINK YOU KNOW ME; (2) how Google’s AdWords algorithm creates and manages a linguistic capitalism as investigated by Pip Thornton’s {poem}.py; and (3) how the style of generative text is becoming both recognizable and re-mixable, forming a machine learning rhetoric, evident twitter user @KeatonPatti’s viral “Olive Garden Tweet.” Refraining from presenting a closed conclusion, we instead speculate the relevance of our data-realist approach by presenting an e-lit meditation of the concept, taking the form of the latest iteration of The Poetry Machine: “The Oracle from Selphie.”

AB - In this forward-looking and somewhat tentative call for a realism of data - or a data-realism - we chart out three literary experiments all relating to one of the most pressing aspects of the contemporary conditions of writing, namely the role of data-driven support software including machine learning. Questioning how to read the text’s data - or the data’s text - we develop our approach in dialogue with three works of e-lit, arguing that these works present three distinct, yet related, ways of engaging with the underlying data-infrastructures of computerized language. Thus, we read these three works of e-lit in order to examine (1) how predictive keyboards change the notion of who is writing (or texting) whom in Erica Scourti’s THINK YOU KNOW ME; (2) how Google’s AdWords algorithm creates and manages a linguistic capitalism as investigated by Pip Thornton’s {poem}.py; and (3) how the style of generative text is becoming both recognizable and re-mixable, forming a machine learning rhetoric, evident twitter user @KeatonPatti’s viral “Olive Garden Tweet.” Refraining from presenting a closed conclusion, we instead speculate the relevance of our data-realist approach by presenting an e-lit meditation of the concept, taking the form of the latest iteration of The Poetry Machine: “The Oracle from Selphie.”

KW - realism

KW - data aesthetics

KW - Electronic literature

U2 - 10.7273/n381-mk15

DO - 10.7273/n381-mk15

M3 - Journal article

JO - Electronic Book Review

JF - Electronic Book Review

SN - 1553-1139

ER -