Systems and methods for demoting links to low-quality webpages

A system comprising:

• a sampling module, stored in memory, that samples user-provided links from an online system;
• a receiving module, stored in memory, that receives, from at least one human labeler for each of the user-provided links, at least one label indicating whether the human labeler considers a landing page of the user-provided link to be a low-quality webpage;
• a deriving module, stored in memory, that derives, from a landing page of each of the user-provided links, landing-page features of the user-provided link;
• a training module, stored in memory, that uses the label and the landing-page features of each of the user-provided links to train a model configured to predict a likelihood that a user-provided link is to a low-quality webpage;
• an identifying module, stored in memory, that identifies user-provided content items that are candidates for a content feed of a user of the online system;
• an applying module, stored in memory, that applies the model to a link of each of the user-provided content items to determine a ranking of the user-provided content items;
• a displaying module, stored in memory, that displays the user-provided content items in the content feed of the user based at least in part on the ranking;
• and
• at least one physical processor configured to execute the sampling module, the receiving module, the deriving module, the training module, the identifying module, the applying module, and the displaying module.

A computer-readable medium comprising computer-readable instructions that, when executed by at least one processor of a computing device, cause the computing device to:

• sample user-provided links from an online system;
• receive, from at least one human labeler for each of the user-provided links, at least one label indicating whether the human labeler considers a landing page of the user-provided link to be a low-quality webpage;
• derive, from a landing page of each of the user-provided links, landing-page features of the user-provided link;
• use the label and the landing-page features of each of the user-provided links to train a model configured to predict a likelihood that a user-provided link is to a low-quality webpage;
• identify user-provided content items that are candidates for a content feed of a user of the online system;
• apply the model to a link of each of the user-provided content items to determine a ranking of the user-provided content items;
• and
• display the user-provided content items in the content feed of the user based at least in part on the ranking.