The Datafied Society. Studying Culture through Data

Es, Karin van; Schäfer, Mirko Tobias

doi:10.5117/9789462981362

Cited by 53 publications

(12 citation statements)

References 10 publications

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“…Faced with these inherent characteristics, the calls for transparency of algorithmic systems, initially aiming towards total transparency, have shifted their focus significantly. Paßmann and Boersma (2017), differentiate between two notions of transparency. Formalised transparency, which would like to see more inside the content of the black box and 'obtain more positive knowledge' (p.140) and practical transparency, which does not try to open the black box, but to 'develop skills without raising the issue of openability' (ibid.).…”

Section: Practical Ai Transparencymentioning

confidence: 99%

“…Faced with the above-mentioned challenges, one of the strategies created, tested and employed was to work with what is available and be creative in finding ways to do research relying on the affordances of platforms themselves and repurposing transparency and regulatory tools as objects for/of study. 1 We define these approaches as letting the platforms speak and making the platforms speak, focusing on achieving practical transparency (Paßmann and Boersma, 2017) through investigating algorithms in action and studying them by observing their outputs and effects.…”

Section: Statesmentioning

confidence: 99%

“…We do this by using a mixed method design for which we developed and adopted two approaches: letting the platforms speak and making the platforms speak. This led to an investigation on two levels, interface and software, while employing two corresponding overarching methods, technography and digital methods (Rogers, 2017). Experimenting with this methodological setup, our experience and results show that, while there are limitations, this approach enables an in-depth critical inquiry and generates valuable new insights into the processes of algorithmic construction of identity, data extraction and inferential analytics.…”

Section: Introductionmentioning

confidence: 99%

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Practical AI Transparency

Stefanija

Pierson²

2020

jdsr

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How does one do research on algorithms and their outputs when confronted with the inherent algorithmic opacity and black box-ness as well as with the limitations of API-based research and the data access gaps imposed by platforms’ gate-keeping practices? This article outlines the methodological steps we undertook to manoeuvre around the above-mentioned obstacles. It is a “byproduct” of our investigation into datafication and the way how algorithmic identities are being produced for personalisation, ad delivery and recommendation. Following Paßmann and Boersma’s (2017) suggestion for pursuing “practical transparency” and focusing on particular actors, we experiment with different avenues of research. We develop and employ an approach of letting the platforms speak and making the platforms speak. In doing so, we also use non-traditional research tools, such as transparency and regulatory tools, and repurpose them as objects of/for study. Empirically testing the applicability of this integrated approach, we elaborate on the possibilities it offers for the study of algorithmic systems, while being aware and cognizant of its limitations and shortcomings.

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Section: Practical Ai Transparencymentioning

confidence: 99%

Section: Statesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Practical AI Transparency

Stefanija

Pierson²

2020

jdsr

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“…In recent years, studies have revealed that these systems have an increasing capacity to (re)produce and amplify already discriminatory practices. Their asymmetric power structures can further obscure the fostering of new divides in data access, interpretation, representation and ethics (Leurs and Shepherd, 2017). This can increase social inequality as their automating function becomes normalized.…”

Section: From E-governance To Datafication: Concerns On Inclusion Pamentioning

confidence: 99%

Benign dataveillance? Examining novel data-driven governance systems in India and China

Arora¹

2019

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This study examines novel data-driven models of governance emerging from the Global South, specifically India and China, enabled by Net-based technologies. The first model, the biometric identity scheme or ‘Aadhaar’ project in India consolidates citizens’ digital identities to enable access to government services such as welfare benefits. The second model is China’s Social Credit System. By combining the citizens’ financial records, online shopping data, social media behaviour and employment history, the system will produce a personal score for each citizen. This rating system will be used to measure the citizens’ trustworthiness. This research unpacks these value-embedded systems posited as digital innovations to strengthen citizenship through new forms of political participation, inclusion and representation. In doing so, we are confronted with what constitutes as “democracy” in this datafied and global era, beyond the universalisms that are on offer today.

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“…Evidentemente todo ello ha merecido reflexiones en profundidad sobre la analítica web (Maldonado, 2015) y las dificultades y desafíos que comporta el nuevo entorno en dicho sentido (Madinaveitia y Merchante 2015).…”

Section: Introductionunclassified

Métricas de comportamiento y sentimientos para la gestión y producción de contenidos audiovisuales

Guadalupe

García

2018

Fonseca, Journal of Communication

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En el presente artículo se analizan las principales métricas de comportamiento y sentimientos utilizadas en el entorno digital y su incidencia en la gestión y producción de contenidos audiovisuales. Los objetivos son: 1) identificar las métricas e indicadores empleados para detectar experiencias y sentimientos de los consumidores; 2) categorizar los indicadores utilizados; y 3) observar en qué medida dichos indicadores inciden en la gestión y producción de contenidos. Para ello se han seleccionados las principales herramientas de medición, se han identificado los indicadores utilizados en cada una de ellas, se ha evaluado las aportaciones que realizan y se han catalogado en atención a los servicios que prestan. La conclusión es que las métricas de comportamiento y sentimientos aportan una nueva manera de entender la capacidad de influencia de los contenidos en los usuarios o espectadores, repercutiendo en aspectos esenciales a la hora de producir contenidos con cierta predicción de éxito.

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The Datafied Society. Studying Culture through Data

Cited by 53 publications

References 10 publications

Practical AI Transparency

Practical AI Transparency

Benign dataveillance? Examining novel data-driven governance systems in India and China

Métricas de comportamiento y sentimientos para la gestión y producción de contenidos audiovisuales

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