Weighted Engagement Scoring

Overview

Calculate a composite engagement score E = sum(w_i * x_i) from multiple heterogeneous signals (votes, ratios, comment volume, sentiment quality, temporal recency) by normalizing each to a common scale and combining via documented weights. The core principle: raw engagement metrics on different scales cannot be meaningfully combined without normalization, and weights without documented rationale are arbitrary.

When to Use

• Multiple engagement signals available (score, upvote ratio, comment count, sentiment, timestamps) and need a single ranking metric
• Raw metrics are on incompatible scales (e.g., scores in thousands, ratios 0-1, comment counts in tens)
• Need to identify representative high-value content from a corpus
• Sorting by a single metric (e.g., top score) misses important content that excels on other dimensions
• Downstream analysis requires a ranked subset of "most engaged" or "most influential" content

When NOT to use:

• Only one engagement metric is available (just sort by that metric)
• Comparing scores across different platforms or communities without recalibrating weights
• Ranking users rather than content (engagement scoring measures content reception, not user quality)
• Content quality assessment without a sentiment or quality signal (engagement != quality)