7. A non-transitory computer-readable medium having instructions stored thereon, the instructions, when executed by one or more processors, cause the processors to perform operations comprising: calculating a current value of a respective approval ratio for each of a plurality of content submissions, the respective approval ratio being a proportion of approval votes among all votes currently accumulated for the content submission; calculating a statistical lower bound for the respective approval ratio of each content submission according to a first scaling method, wherein the first scaling method scales down the current value of the respective approval ratio by a decreasing amount with an increasing vote count for the content submission; generating an approval ranking for the plurality of content submissions according to the statistical lower bound calculated for the respective approval ratio of each of the content submissions; calculating a statistical upper bound for the respective approval ratio of each content submission according to a second scaling method, wherein the second scaling method scales up the current value of the respective approval ratio by a decreasing amount with an increasing vote count for the content submission; generating a voting priority ranking for the plurality of content submissions according to the statistical upper bound calculated for the respective approval ratio of each content submission; and selecting one or more content submissions in the voting priority ranking as featured content submissions for additional voting according to respective ranks of the one or more content submissions in the voting priority ranking.
7. A non-transitory computer-readable medium having instructions stored thereon, the instructions, when executed by one or more processors, cause the processors to perform operations comprising: calculating a current value of a respective approval ratio for each of a plurality of content submissions, the respective approval ratio being a proportion of approval votes among all votes currently accumulated for the content submission; calculating a statistical lower bound for the respective approval ratio of each content submission according to a first scaling method, wherein the first scaling method scales down the current value of the respective approval ratio by a decreasing amount with an increasing vote count for the content submission; generating an approval ranking for the plurality of content submissions according to the statistical lower bound calculated for the respective approval ratio of each of the content submissions; calculating a statistical upper bound for the respective approval ratio of each content submission according to a second scaling method, wherein the second scaling method scales up the current value of the respective approval ratio by a decreasing amount with an increasing vote count for the content submission; generating a voting priority ranking for the plurality of content submissions according to the statistical upper bound calculated for the respective approval ratio of each content submission; and selecting one or more content submissions in the voting priority ranking as featured content submissions for additional voting according to respective ranks of the one or more content submissions in the voting priority ranking. 8. The computer-readable medium of claim 7 , wherein the first scaling method scales the current value of the respective approval ratio to a lower bound of a Wilson score interval calculated for the current value of the respective approval ratio.