Using Polling Results as Discrete Metrics For Content Quality Prediction Model

A non-transitory computer-readable storage medium storing instructions, the instructions when executed by a processor in a social networking system for predicting quality of content items, causes the processor to:

• determine interests for each of a plurality of users of a social networking system, a respective interest for each user based on information provided by the respective user;
• infer a preference of each user for a first content item over a second content item in a pair-wise comparison of the first and second content items, the inferring based on at least one of the determined interests for the respective user;
• identify at least one predictive factor associated with each inferred preference;
• for each identified predictive factor, determine a feedback coefficient for the identified predictive factor based on at least a subset of the inferred preferences;
• and
• store the feedback coefficients for the identified predictive factors in a computer-readable storage medium.

A system comprising:

• a processor;
• a non-transitory computer readable storage medium for storing software modules;
• and
• a polling analysis module configured to:
• determine interests for each of a plurality of users of a social networking system, a respective interest for each user based on information provided by the respective user;
• infer a preference of each user for a first content item over a second content item in a pair-wise comparison of the first and second content items, the inferring based on at least one of the determined interests for the respective user;
• identify at least one predictive factor associated with each inferred preference;
• for each identified predictive factor, determine a feedback coefficient for the identified predictive factor based on at least a subset of the inferred preferences;
• and
• store the feedback coefficients for the identified predictive factors in a computer-readable storage medium.