June 18 2021 / Meeting amsterdam – The Digital Services Act Observatory at the Amsterdam Law School will be hosting events on a variety of topics which are relevant to the DSA discussion and process. Information on these events will be posted here.
Please get in touch if you would like to share your ideas for a DSA-related event or discuss your research at one of our events.
Uva researchers Natali Helberger, Max van Drunen, Sanne Vrijenhoek and Judith Möller wrote a commentary on the Internet Policy Review on “Regulation of news recommenders in the Digital Services Act: empowering David against the Very Large Online Goliath”.
Nowadays it is difficult to imagine the online world without recommendation algorithms. They filter and classify the growing abundance of information, prioritising content according to predefined ranking criteria. The result of that process is a recommendation to users on what content best matches their interests or personal profile. We encounter recommendation algorithms on a daily basis. They suggest products and services on e-commerce websites such as Amazon, help finding the love of your life on a dating platform, help you discover music and films on services such as Spotify or Netflix, give personalised recommendations on news websites, and match you with content on social media platforms such as YouTube and Facebook. As such, recommender algorithms are the engines behind the internet’s knowledge infrastructure.
Because of their importance … [ read more ]
Uva researchers Natali Helberger, Max van Drunen, Sanne Vrijenhoek and Judith Möller wrote a commentary on the Internet Policy Review on “Regulation of news recommenders in the Digital Services Act: empowering David against the Very Large Online Goliath”.
Nowadays it is difficult to imagine the online world without recommendation algorithms. They filter and classify the growing abundance of information, prioritising content according to predefined ranking criteria. The result of that process is a recommendation to users on what content best matches their interests or personal profile. We encounter recommendation algorithms on a daily basis. They suggest products and services on e-commerce websites such as Amazon, help finding the love of your life on a dating platform, help you discover music and films on services such as Spotify or Netflix, give personalised recommendations on news websites, and match you with content on social media platforms such as YouTube and Facebook. As such, recommender algorithms are the engines behind the internet’s knowledge infrastructure.
Because of their importance … [ read more ]
Uva researchers Natali Helberger, Max van Drunen, Sanne Vrijenhoek and Judith Möller wrote a commentary on the Internet Policy Review on “Regulation of news recommenders in the Digital Services Act: empowering David against the Very Large Online Goliath”.
Nowadays it is difficult to imagine the online world without recommendation algorithms. They filter and classify the growing abundance of information, prioritising content according to predefined ranking criteria. The result of that process is a recommendation to users on what content best matches their interests or personal profile. We encounter recommendation algorithms on a daily basis. They suggest products and services on e-commerce websites such as Amazon, help finding the love of your life on a dating platform, help you discover music and films on services such as Spotify or Netflix, give personalised recommendations on news websites, and match you with content on social media platforms such as YouTube and Facebook. As such, recommender algorithms are the engines behind the internet’s knowledge infrastructure.
Because of their importance … [ read more ]
Uva researchers Natali Helberger, Max van Drunen, Sanne Vrijenhoek and Judith Möller wrote a commentary on the Internet Policy Review on “Regulation of news recommenders in the Digital Services Act: empowering David against the Very Large Online Goliath”.
Nowadays it is difficult to imagine the online world without recommendation algorithms. They filter and classify the growing abundance of information, prioritising content according to predefined ranking criteria. The result of that process is a recommendation to users on what content best matches their interests or personal profile. We encounter recommendation algorithms on a daily basis. They suggest products and services on e-commerce websites such as Amazon, help finding the love of your life on a dating platform, help you discover music and films on services such as Spotify or Netflix, give personalised recommendations on news websites, and match you with content on social media platforms such as YouTube and Facebook. As such, recommender algorithms are the engines behind the internet’s knowledge infrastructure.
Because of their importance … [ read more ]
Uva researchers Natali Helberger, Max van Drunen, Sanne Vrijenhoek and Judith Möller wrote a commentary on the Internet Policy Review on “Regulation of news recommenders in the Digital Services Act: empowering David against the Very Large Online Goliath”.
Nowadays it is difficult to imagine the online world without recommendation algorithms. They filter and classify the growing abundance of information, prioritising content according to predefined ranking criteria. The result of that process is a recommendation to users on what content best matches their interests or personal profile. We encounter recommendation algorithms on a daily basis. They suggest products and services on e-commerce websites such as Amazon, help finding the love of your life on a dating platform, help you discover music and films on services such as Spotify or Netflix, give personalised recommendations on news websites, and match you with content on social media platforms such as YouTube and Facebook. As such, recommender algorithms are the engines behind the internet’s knowledge infrastructure.
Because of their importance … [ read more ]
Nowadays it is difficult to imagine the online world without recommendation algorithms. They filter and classify the growing abundance of information, prioritising content according to predefined ranking criteria. The result of that process is a recommendation to users on what content best matches their interests or personal profile. We encounter recommendation algorithms on a daily basis. They suggest products and services on e-commerce websites such as Amazon, help finding the love of your life on a dating platform, help you discover music and films on services such as Spotify or Netflix, give personalised recommendations on news websites, and match you with content on social media platforms such as YouTube and Facebook. As such, recommender algorithms are the engines behind the internet’s knowledge infrastructure.
Because of their importance … [ read more ]
May 23 2021 / online meeting at 21:00 central europe time about …
Nowadays it is difficult to imagine the online world without recommendation algorithms. They filter and classify the growing abundance of information, prioritising content according to predefined ranking criteria. The result of that process is a recommendation to users on what content best matches their interests or personal profile. We encounter recommendation algorithms on a daily basis. They suggest products and services on e-commerce websites such as Amazon, help finding the love of your life on a dating platform, help you discover music and films on services such as Spotify or Netflix, give personalised recommendations on news websites, and match you with content on social media platforms such as YouTube and Facebook. As such, recommender algorithms are the engines behind the internet’s knowledge infrastructure.
April 14 2021 / Nowadays it is difficult to imagine the online world without recommendation algorithms. They filter and classify the growing abundance of information, prioritising content according to predefined ranking criteria. The result of that process is a recommendation to users on what content best matches their interests or personal profile. We encounter recommendation algorithms on a daily basis. They suggest products and services on e-commerce websites such as Amazon, help finding the love of your life on a dating platform, help you discover music and films on services such as Spotify or Netflix, give personalised recommendations on news websites, and match you with content on social media platforms such as YouTube and Facebook. As such, recommender algorithms are the engines behind the internet’s knowledge infrastructure.
No events planned
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