What is algorithmic curation in internet information filtering?

Algorithmic curation is the selection, organization, and presentation of digital content on online platforms using recommendation systems and personalized search. It relies on approaches like collaborative filtering and content-based filtering to tailor feeds and search results to individual users. While it helps users discover content, it can also lead to filter bubbles and intellectual isolation by reinforcing existing beliefs.

What we know

• Algorithmic curation involves selecting and organizing online media through technologies like recommender systems and personalized search based on inferred user interests. [1, 2]
• Curation algorithms implement different filter approaches, including collaborative filtering and content-based filtering. [2]
• Personalized searches and algorithmic curation can create filter bubbles, which cause intellectual isolation by exposing users primarily to information that reinforces existing beliefs. [5]
• Examples of products that use algorithmic curation include search engines and social media feeds such as those on Twitter and Facebook. [2]

Still open

• The precise scale, direction, and long-term societal effects of algorithmic systems on phenomena like political polarization remain debated, in part because independent researchers have limited access to platform systems.

Where to go next

• how it workedHow do recommendation systems increase content visibility?
• what followedWhat is a filter bubble?
• a case in pointHow do social media platforms use recommender systems?
• the bigger pictureHow are recommendation systems regulated globally?
• an unexpected connectionWhat is the dead Internet theory?

Sources

• [1]algorithmic curation (Wikidata Q117012236) · CC0 1.0
• [2]Algorithmic curation · CC BY-SA 4.0
• [3]Dead Internet theory · CC BY-SA 4.0
• [4]Algorithmic amplification · CC BY-SA 4.0
• [5]Filter bubble · CC BY-SA 4.0