Add majority-vocabulary section: top-3 words per tag on the balanced subset (>50% rule)

README.md

@@ -228,6 +228,33 @@ measures weaker on the probes above. The other 1,768 rows are human labels. `lab
 marks which is which; model and human error are not comparable across it, and the `anger`/`contempt`
 rows are the noisier subset.
 
+## Majority vocabulary of the balanced subset
+
+Which words actually belong to which tag, measured on the `balanced` config (1,260 rows = 180 x 7).
+A word enters a tag's list only if **more than 50% of its corpus-wide occurrences** (distinct tweets)
+sit in that one tag; anything left over in other tags is tolerated. Stopwords (Sastrawi + colloquial),
+laughter (`wkwk`, `haha`), URLs and mentions are removed; words in fewer than 2 distinct tweets are
+dropped. df = distinct tweets containing the word; share = df in the tag / df corpus-wide.
+
+| tag | majority words | top 3 (df, share) |
+|---|---|---|
+| `anger` | 86 | `kesal` 46 (53%) · `murka` 34 (56%) · `azab` 3 (75%) |
+| `contempt` | 39 | `paling` 10 (59%) · `mati` 6 (60%) · `gatau` 5 (62%) |
+| `disgust` | 43 | `jijik` 63 (84%) · `risih` 49 (92%) · `muak` 47 (70%) |
+| `enjoyment` | 44 | `bangga` 40 (95%) · `senang` 33 (79%) · `syukur` 29 (100%) |
+| `fear` | 45 | `ngeri` 62 (97%) · `takut` 52 (70%) · `gugup` 44 (90%) |
+| `sadness` | 67 | `kecewa` 63 (77%) · `duka` 42 (91%) · `sedih` 28 (70%) |
+| `surprise` | 44 | `heran` 67 (84%) · `terkejut` 58 (84%) · `terpesona` 34 (92%) |
+
+The five classes EmoTweetID sampled and tagged by keyword recover exactly that keyword lexicon
+(`takut`, `sedih`, `heran`, `jijik`, ...). The two classes split here do not: of the corpus's own
+anger vocabulary only `kesal` (53%) and `murka` (56%) hold a majority in `anger` - `muak` lands in
+`disgust` (70%), `kesel` ties at exactly 50% and enters no list, and `benci` (48% in `contempt`),
+`tersinggung` (44% in `contempt`) and `marah` (30% in `anger`) have no majority anywhere. The
+sharpest finding on this card, seen from the vocabulary side: the words that most plainly mean
+anger in Indonesian are shared between the two classes, and where they lean at all, they lean
+`contempt`. Anger's third word comes from a 12-way tie at df=3 (`azab` takes it alphabetically).
+
 ## Schema
 
 | field | type | meaning |