NewsGuru - Methodology

Significance Scoring Methodology

Significance Heatmap Overview

The significance heatmap visualizes news coverage from the last 24 hours, based on article volume and average significance scores. It is rendered as an interactive Plotly treemap.

Key Metrics

Size of each block: Proportional to the number of articles in that topic.
Color gradient: From light gray (low significance, ~0-3) to dark red (high significance, ~7-10).
Data source: Aggregated from RSS feeds and web searches across Estonian and English news sources.

7-Factor Scoring Methodology

Each article is scored by an LLM on seven dimensions, combined into a single 0-10 significance score:

Factor	Weight	Description
Scale	4/20	How broadly does the event affect people?
Impact	4/20	How strong is the immediate, tangible effect?
Novelty	3/20	How unique and unexpected is this event?
Potential	3/20	How likely is this to shape the future?
Legacy	3/20	How likely to be remembered as a turning point?
Positivity	1/20	Counteracts negativity bias in news coverage.
Credibility	2/20	How trustworthy and well-sourced is the report?

Why Positivity?

News sources overreport negative events. This factor (weight 1/20) brings the ratio closer to 50:50 in the high-significance range, surfacing scientific discoveries and tech advancements alongside wars and disasters.

Expected Distribution

0-2: Sports results, entertainment, minor local news (~60% of articles)
3-4: Regional politics, business earnings, routine policy changes (~25%)
5-6: Significant national events, major policy shifts, scientific findings (~10%)
7-8: Major world events, landmark decisions, breakthroughs (~4%)
9-10: Once-in-a-decade events, paradigm shifts (~1%)

Philosophy

Significance is objective — it measures how much an event affects humanity as a whole. This is different from importance, which is subjective. If nothing significant happens, the feed is short by design.