Update README.md

README.md

@@ -1,28 +1,180 @@
 ---
-dataset_info:
-  features:
-  - name: MBTI
-    dtype: string
-  - name: Emotion
-    dtype: string
-  - name: Language
-    dtype: string
-  - name: Style
-    dtype: string
-  - name: Text
-    dtype: string
-  splits:
-  - name: train
-    num_bytes: 40649078
-    num_examples: 112480
-  download_size: 24578090
-  dataset_size: 40649078
-configs:
-- config_name: default
-  data_files:
-  - split: train
-    path: data/train-*
+license: cc-by-nc-4.0
+task_categories:
+  - text-classification
 language:
-- en
-- id
+  - en
+  - id
+  - ja
+  - ko
+  - es
+  - fr
+  - de
+  - zh
+  - pt
+  - ru
+  - it
+tags:
+  - music
+  - lyrics
+  - emotion
+  - go-emotions
+  - mbti
+  - personality
+  - multilingual
+  - math-rock
+  - midwest-emo
+  - synthetic
+size_categories:
+  - 100K<n<1M
+pretty_name: Multilingual Math Rock Lyrics for Emotion and MBTI Classification
+configs:
+  - config_name: default
+    data_files:
+      - split: train
+        path: train-00000-of-00001.parquet
 ---
+
+# Multilingual Math Rock Lyrics for Emotion and MBTI Classification
+
+## Dataset Summary
+
+This dataset contains **120,015** song-lyric passages annotated with two independent
+classification targets: a fine-grained **emotion** label (28 categories based on the
+GoEmotions taxonomy) and a **Myers-Briggs Type Indicator (MBTI)** personality type
+(16 categories). All passages are written in the stylistic register of the
+**math rock** and **midwest emo** genres and span eleven languages.
+
+The corpus was built to train two multilingual text classifiers,
+[`anggars/xlm-emotion`](https://huggingface.co/anggars/xlm-emotion) and
+[`anggars/xlm-mbti`](https://huggingface.co/anggars/xlm-mbti), which form the textual
+branch of a broader multimodal emotion-and-personality analysis system.
+
+> **Composition notice.** The overwhelming majority of the passages are **synthetic**,
+> generated with the **Gemma** large language model, while a small set of authentic
+> lyrics was retrieved from public sources. See [Data Sources](#data-sources) for exact
+> counts. The dataset is intended for research and educational use only.
+
+## Supported Tasks
+
+- **Emotion classification** (`text-classification`): predict one of 28 emotion
+  categories from a lyric passage.
+- **MBTI personality classification** (`text-classification`): predict one of 16 MBTI
+  personality types from a lyric passage.
+
+The two targets are provided as separate columns and are meant to be trained as two
+independent single-label classifiers.
+
+## Languages
+
+The `Text` field is multilingual. The approximate distribution is:
+
+| Language | Code | Rows | Share |
+| --- | --- | ---: | ---: |
+| English | en | 41,759 | 34.79% |
+| Indonesian | id | 25,176 | 20.98% |
+| Japanese | ja | 13,647 | 11.37% |
+| Korean | ko | 9,974 | 8.31% |
+| Spanish | es | 8,514 | 7.09% |
+| French | fr | 7,019 | 5.85% |
+| German | de | 4,112 | 3.43% |
+| Chinese | zh | 4,080 | 3.40% |
+| Portuguese | pt | 2,890 | 2.41% |
+| Russian | ru | 2,843 | 2.37% |
+| Italian | it | 1 | <0.01% |
+| **Total** | | **120,015** | **100%** |
+
+## Dataset Structure
+
+### Data Fields
+
+| Field | Type | Description |
+| --- | --- | --- |
+| `Text` | string | The lyric passage. |
+| `Emotion` | string | One of 28 GoEmotions categories (see below). |
+| `MBTI` | string | One of 16 MBTI personality types (see below). |
+| `Language` | string | ISO 639-1 language code of `Text`. |
+| `Style` | string | Genre register of the passage (math rock / midwest emo). |
+| `source` | string | Provenance of the row: `synthetic_gemma` or `genius_real`. |
+| `Title` | string | Song title (populated for authentic rows; may be empty for synthetic rows). |
+| `Artist` | string | Performing artist (populated for authentic rows; may be empty for synthetic rows). |
+
+### Data Splits
+
+The dataset ships as a single `train` split. Users are expected to create their own
+validation and test partitions (for example, a stratified 80/20 split with a fixed seed).
+
+| Split | Rows |
+| --- | ---: |
+| train | 120,015 |
+
+## Class Labels
+
+### Emotion (28 categories, GoEmotions taxonomy)
+
+`admiration`, `amusement`, `anger`, `annoyance`, `approval`, `caring`, `confusion`,
+`curiosity`, `desire`, `disappointment`, `disapproval`, `disgust`, `embarrassment`,
+`excitement`, `fear`, `gratitude`, `grief`, `joy`, `love`, `nervousness`, `optimism`,
+`pride`, `realization`, `relief`, `remorse`, `sadness`, `surprise`, `neutral`
+
+The emotion labels are approximately balanced, with roughly **4,280 to 4,290** rows per
+category.
+
+### MBTI (16 personality types)
+
+`INTJ`, `INTP`, `ENTJ`, `ENTP`, `INFJ`, `INFP`, `ENFJ`, `ENFP`,
+`ISTJ`, `ISFJ`, `ESTJ`, `ESFJ`, `ISTP`, `ISFP`, `ESTP`, `ESFP`
+
+The MBTI labels are approximately balanced, with roughly **7,498 to 7,504** rows per type.
+
+## Data Sources
+
+| Source | Rows | Share | Description |
+| --- | ---: | ---: | --- |
+| `synthetic_gemma` | 119,922 | 99.92% | Passages generated with the Gemma large language model. |
+| `genius_real` | 93 | 0.08% | Authentic lyrics retrieved from public sources. |
+| **Total** | **120,015** | **100%** | |
+
+## Data Collection and Processing
+
+1. **Authentic lyric retrieval.** A limited pool of genuine math rock and midwest emo
+   lyrics was collected from public lyric providers, then cleaned and language-tagged.
+2. **Synthetic generation.** To reach a balanced, large-scale corpus, the remaining
+   passages were generated with the Gemma large language model, conditioned on a target
+   emotion category, a target MBTI type, a target language, and the math rock / midwest
+   emo stylistic register.
+3. **Labeling and balancing.** Each row carries an emotion label and an MBTI label. The
+   final corpus was merged, de-duplicated on `Text`, and shuffled with a fixed random
+   seed to produce an approximately balanced distribution across both label sets.
+
+## Intended Uses
+
+This dataset is designed for:
+
+- Fine-tuning multilingual transformer classifiers for lyric-level emotion recognition.
+- Fine-tuning multilingual transformer classifiers for exploratory MBTI inference from text.
+- Research on affective and stylistic modeling of the math rock and midwest emo genres.
+
+## Limitations and Biases
+
+- **Predominantly synthetic.** About 99.9% of the passages are machine-generated rather
+  than authored by human songwriters. Models trained on this corpus may learn artifacts
+  of the generating model instead of genuine lyric phenomena.
+- **Weak MBTI supervision.** MBTI is a self-report typology with limited scientific
+  validity, and the labels here are assigned as exploratory proxies rather than
+  clinically validated annotations. Results should be interpreted cautiously.
+- **Genre and length skew.** Passages are constrained to a narrow stylistic register and
+  may not generalize to other genres or to full-length songs.
+- **Uneven language coverage.** English and Indonesian dominate the corpus, and some
+  languages (for example, Italian) are represented by only a handful of rows.
+- **Copyright.** Authentic passages remain the property of their respective rights
+  holders and are included in limited quantity for research purposes only.
+
+## Citation
+
+If you use this dataset, please cite the associated undergraduate thesis project on
+multimodal emotion and MBTI analysis of math rock music.
+
+## License
+
+Released under **CC BY-NC 4.0** for non-commercial research and educational use.