ALEX
Financiado
ALgorithms EXposed. Investigating Automated Personalization and Filtering for Re...
ALgorithms EXposed. Investigating Automated Personalization and Filtering for Research and Activism
Personalization algorithms—filtering content on the basis of someone's profile—increasingly mediate the web experience of users. By forging a specific reality for each individual, they silently shape customized 'information diets'...
Personalization algorithms—filtering content on the basis of someone's profile—increasingly mediate the web experience of users. By forging a specific reality for each individual, they silently shape customized 'information diets': in other words, they determine which news, opinions and rumors users are exposed to. Restricting users’ possibilities, they ultimately infringe on their agency. As exposed by the recent Cambridge Analytica scandal, they are supported by questionable data sharing practices at the core of the business models of the social media industry. Yet, personalization algorithms are proprietary and thus remain inaccessible to end users. The few experiments auditing these algorithms rely on data provided by platform companies themselves. They are highly technical, hardly scalable, and fail to put social media users in the driver seat. The ALgorithms EXposed (ALEX) project aims at unmasking the functioning of personalization algorithms on social media platforms, taking Facebook as a test case. It is 'data activism' in practice, as it uses publicly available data for awareness raising and citizen empowerment. ALEX will pursue five goals: 1) software development and stabilization, building on the alpha version of facebook.tracking.exposed (fbtrex), a working prototype of a browser extension analyzing the outcomes of Facebook's News Feed algorithms; 2) the release of two spin-off products building on fbtrex, namely AudIT, enabling researchers to do expert analysis on algorithmic biases, and RealityCheck, allowing users to monitor their own social media consumption patterns; 3) testing the technical feasibility of adapting the ALEX approach to analyze algorithmic personalization on other platforms such as Twitter and Google; 4) the design and organization of data literacy modules on algorithmic personalization, and 5) the launch of a consultancy service to promote tool take-up and the future sustainability of the project.
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Duración del proyecto: 15 meses
Fecha Inicio: 2018-11-19
Fecha Fin: 2020-02-29
Fecha Fin: 2020-02-29
Línea de financiación: concedida
El organismo H2020 notifico la concesión del proyecto el día 2020-02-29
Línea de financiación objetivo
El proyecto se financió a través de la siguiente ayuda:
ERC-2018-PoC:
ERC Proof of Concept Grant
Cerrada
hace 6 años
Presupuesto
El presupuesto total del proyecto asciende a
150K€
Líder del proyecto
UNIVERSITEIT VAN AMSTERDAM
No se ha especificado una descripción o un objeto social para esta compañía.
Perfil tecnológico
TRL
4-5
Perfil tecnológico
TRL
4-5
1.46M€ |
Participante