Improved Online Wilson Score Interval Method for Community Answer Quality Ranking

In this paper, a fast and easy-to-deploy method with a strong interpretability for community answer quality ranking is proposed. This method is improved based on the Wilson score interval method [Wilson, 1927], which retains its advantages and simultaneously improve the degree of satisfaction with the ranking of the high-quality answers. The improved answer quality score considers both Wilson score interval and the spotlight index, the latter of which will be introduced in the article. This method could significantly improve the ranking of the best answers with high attention in diverse scenarios.

💡 Research Summary

The paper proposes an enhanced ranking metric for community Q&A platforms that builds on the classic Wilson score interval while addressing its known shortcomings. The Wilson interval provides a conservative lower‑bound estimate of answer quality based solely on the up‑vote/down‑vote ratio and total vote count, which works well for small samples but tends to undervalue answers that receive many votes of both types (e.g., controversial or highly discussed posts). To remedy this, the authors introduce the Spotlight Index (SI), a normalized measure of an answer’s “attention” relative to the most‑voted answer within the same question. SI is defined as the answer’s vote count divided by the maximum vote count (NOP) and therefore ranges from 0 to 1. Several variants are described: Whole SI (total votes), Net SI (net votes), Positive SI (up‑votes of the top‑up‑voted answer), Negative SI (down‑votes of the top‑down‑voted answer), Up‑vote Index, and Down‑vote Index. Non‑linear extensions (logarithmic, exponential, polynomial) are also discussed to control how quickly SI grows with additional votes.

The final score is a weighted average of the Wilson lower bound and the chosen SI:
Score = M · Wilson_Lower + (1 − M) · SI,
where M∈