Vector Analysis Methodology
What vectors represent
In The Wire's analytical framework, a "vector" is a directional signal extracted from a source's content at a specific point in time. It has three components:
- Direction — bullish, bearish, or neutral. This is the AI's classification of what the source is communicating about market conditions in a given category.
- Source — which outlet produced the signal, carrying that outlet's trust score as a credibility weight.
- Timestamp — when the signal was observed, enabling temporal pattern detection.
A single vector in isolation tells you what one source thinks about one topic at one moment. The analytical power comes from examining vectors in aggregate.
Multi-source synthesis
The Wire monitors dozens of sources simultaneously. Each scan produces a matrix of vectors: every source × every category = a signal. From this matrix, The Wire derives:
- Category consensus — do sources agree on the direction for a given topic?
- Cross-category patterns — is the same directional pressure appearing in multiple categories simultaneously?
- Outlier detection — is one source diverging sharply from the consensus?
- Temporal shifts — has a category that was neutral in the last scan shifted to bearish in this one?
How classification works
The AI reads each source's full content — not headlines, not snippets, but the complete published material available at scan time. It classifies the directional sentiment for each relevant category, considering:
- Explicit directional language
- Analytical framing
- Hedged positioning
- Data reporting without editorial stance → neutral
The classification is not keyword matching. It is contextual reading.
From vectors to intelligence
The final scan report transforms the raw vector matrix into readable intelligence. Categories are grouped. Outlets are listed with their signals and trust scores. Convergence alerts fire when the pattern warrants it. The DEFCON level synthesizes the whole picture into a single threat assessment.