1. A computer-implemented method comprising: providing, by a computing device, a subset of a set of content items for user comparison of production quality of the content items of the subset, wherein the subset is selected from the set of content items using active sampling; receiving a user selection of a content item of the subset, wherein the user selection is to indicate user perception of higher relative production quality over other content items of the subset; assembling, by the computing device, data samples corresponding to a plurality of users, the data samples corresponding to user selections, each of the corresponding user selections indicating higher relative production quality within the set of content items; extracting content features from each of the content items in the set; learning, by the computing device based on the data samples from the plurality of users, a statistical model on the extracted content features, wherein learning the statistical model comprises assigning weight factor values to the extracted content features to predict the user selections indicating higher relative production quality for the set of content items; applying, by the computing device, the learned statistical model to extracted content features of another content item that is not part of the set of content items; and assigning, via applying the learned statistical model, a production quality score to the another content item using the assigned weight factor values, the production quality score to indicate the relative production quality of the another content item.