Crypto Research Consensus

WHAT IT DOES. Reads a rolling news-derived dataset scoring each coin's recent article corpus as bullish, bearish, neutral or mixed with source-divergence flags, filters to the tracked assets, and assigns conviction from ARTICLE VOLUME - strong at eight or more articles, then moderate, then weak.

THE CONSTRUCT PROBLEM IS IN THAT LAST STEP, and it is worth working through carefully because the reasoning sounds right.

CONVICTION SHOULD MEAN 'how confident are we in this reading'. Article count measures HOW MUCH WAS WRITTEN. Those come apart immediately: eight articles all rewriting one press release are eight articles and one source, while two genuinely independent, high-quality analyses reaching the same conclusion by different routes can be far more informative. Independence alone does not settle it either - two weak independent analyses are not better than several careful ones, so source quality belongs beside origin count. Volume proxies for confidence only if the articles are independent, and news coverage is notably not - syndication, wire pickup and re-reporting mean a single origin routinely produces many pieces.

WORSE, ARTICLE COUNT TRACKS PROMINENCE. Large, well-known assets are covered constantly, so they clear an eight-article threshold as a matter of course while a smaller holding rarely will. Conviction therefore correlates with market capitalisation, which is not what the word is meant to convey. Read 'strong conviction' as 'widely covered'.

WHAT WOULD IMPROVE THE PROXY: the number of DISTINCT ORIGINS rather than articles, the dispersion of the underlying scores, source quality, and whether independent methods agree. Note that even all of those give a better proxy rather than CALIBRATED confidence, which can only be established by checking past confidence assessments against realised outcomes. The dataset's SOURCE-DIVERGENCE FLAG is the closest thing here to that and is the more informative field - genuine disagreement between sources is real information, and it is the opposite of what a volume threshold rewards.

A STRUCTURAL NOTE. Because the scoring is news-derived, every limit of keyword scoring applies upstream of this: lexicon limits, negation, attribution and the fact that headlines often lag the move they describe. This analysis inherits all of it and adds an aggregation layer. Aggregation can reduce INDEPENDENT noise and so be more reliable than any single article - what it cannot do is remove a bias the inputs SHARE, such as a lexicon's systematic errors or the same story reported ten times.

AND A REMINDER ABOUT AGREEMENT. Concurrence between correlated sources is weaker evidence than concurrence between independent ones. Articles covering the same event are about as correlated as sources get.