2015
DOI: 10.1016/j.compcom.2015.01.005
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The Invisible Digital Identity: Assemblages in Digital Networks

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Cited by 59 publications
(20 citation statements)
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References 11 publications
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“…These include Miguel Sicart's 'second self' (Sicart, 2009), Grant Tavinor's 'fictive self' (Tavinor, 2009), Marie-Laure Ryan's notion of 'narrative memory' informing the outcome of endings in interactive narra- tive (Ryan, 2015), and Barry Atkin's observation that accumulated memory allows a machine to 'see' a user (Atkins, 2013). A similar idea can also be found in the field of software studies, that of Estee Beck's 'invisible digital identity' (Beck, 2016).…”
Section: The Expressed Selfmentioning
confidence: 63%
“…These include Miguel Sicart's 'second self' (Sicart, 2009), Grant Tavinor's 'fictive self' (Tavinor, 2009), Marie-Laure Ryan's notion of 'narrative memory' informing the outcome of endings in interactive narra- tive (Ryan, 2015), and Barry Atkin's observation that accumulated memory allows a machine to 'see' a user (Atkins, 2013). A similar idea can also be found in the field of software studies, that of Estee Beck's 'invisible digital identity' (Beck, 2016).…”
Section: The Expressed Selfmentioning
confidence: 63%
“…Employing an example related to Buffy the Vampire Slayer, Kellner and Share emphasize the subjective and ideological nature of human communication but fail to thoroughly consider how non-human actors might also influence communicative acts in new media. At the same time, the nonhuman exploration of new media appears frequently in the works of digital rhetoric scholars (Beck 2015;Brock 2019;Brown 2015). Our extension of Kellner and Share's model, accordingly, is meant to highlight the complex distribution of subjectivity, ideology, and agency across non-human and human relations.…”
Section: Problematic Information and Critical Media Literacymentioning
confidence: 93%
“…Social media services embed their algorithm into the web system to offer customized and personalized commercials and news feeds to the users as a way to commodify audiences. These automated algorithms seem to be neutral, but they encode human bias and are inherently constructed by designers, programmers, and architects (Beck, ; Gourarie, ). The predetermined algorithms favor certain kinds of participants and participations, thus reinforcing social, economic, and cultural classifications.…”
Section: The Problems Of Consumerist Networked Audiences In Neoliberamentioning
confidence: 99%
“…These automated algorithms seem to be neutral, but they encode human bias and are inherently constructed by designers, programmers, and architects (Beck, 2015;Gourarie, 2016). The predetermined algorithms favor certain kinds of participants and participations, thus reinforcing social, economic, and cultural classifications.…”
Section: The Problems Of Consumerist Networked Audiences In Neolibementioning
confidence: 99%