Add POCAAffectClassification (MTurk GEW-20; z>=1 + top-1; train/test stratified)

README.md

@@ -0,0 +1,155 @@
+---
+license: other
+task_categories:
+- text-classification
+task_ids:
+- multi-label-classification
+language:
+- en
+multilinguality:
+- monolingual
+size_categories:
+- n<1K
+pretty_name: POCAAffectClassification
+tags:
+- poetry
+- english
+- affect
+- emotion-classification
+- multi-label-classification
+- geneva-emotion-wheel
+- mteb
+- poetrymteb
+- embedding-evaluation
+annotations_creators:
+- crowdsourced
+source_datasets:
+- POCA
+configs:
+- config_name: default
+  data_files:
+  - split: train
+    path: data/train-*
+  - split: test
+    path: data/test-*
+  default: true
+dataset_info:
+- config_name: default
+  features:
+  - name: id
+    dtype: string
+  - name: title
+    dtype: string
+  - name: author
+    dtype: string
+  - name: poem
+    dtype: string
+  - name: labels
+    sequence: int64
+  - name: label_names
+    sequence: string
+  - name: scores
+    sequence: float64
+  - name: n_annotators
+    dtype: int64
+  splits:
+  - name: train
+    num_examples: 227
+  - name: test
+    num_examples: 61
+---
+
+# POCAAffectClassification
+
+Multi-label **affect / emotion classification** for English poetry (PoetryMTEB), derived from the [POCA](https://doi.org/10.17863/CAM.73749) dataset (Khan, Hopkins & Gunes, ACII 2021).
+
+Poems are annotated on the **Geneva Emotion Wheel** (20 discrete affects, intensity 0–10) via Mechanical Turk; we binarize to multi-labels for embedding evaluation.
+
+## Dataset Card
+
+| Item | Description |
+|------|-------------|
+| **Source** | POCA supplementary data (`mturk/combined.csv` + `poems/`) |
+| **Paper** | [Multi-dimensional Affect in Poetry (POCA) Dataset](https://doi.org/10.17863/CAM.73749) (ACII 2021); DOI [10.1109/ACII52823.2021.9597451](https://doi.org/10.1109/acii52823.2021.9597451) |
+| **Languages** | English (`en`) |
+| **Unit** | Full poem text |
+| **Labels** | Multi-label subset of **20** affects |
+| **Size** | train=227; test=61 (matched poems with text) |
+| **Splits** | Stratified by primary (highest-mean) affect ≈ 80% / 20%, seed=42 |
+| **Evaluation metrics** | Multi-label classification on embeddings: **macro/micro F1**, **Average Precision (AP)** |
+
+### Label binarization (from score statistics)
+
+MTurk scores are noisy (annotator std ≈ 2.6 on a 0–10 scale) and absolute thresholds leave many empty / over-dense label sets. We therefore use:
+
+1. Aggregate **mean** score per affect across annotators for each poem.
+2. Compute **within-poem z-scores**; keep affects with \(z \ge 1.0\).
+3. Always include the **top-1** affect (guarantees ≥1 label).
+
+Mean labels/poem ≈ 3.12.
+
+## Label taxonomy (20)
+
+| id | label_name | train | test | total |
+|---:|------------|------:|-----:|------:|
+| 0 | `Admiration` | 56 | 11 | 67 |
+| 1 | `Amusement` | 95 | 28 | 123 |
+| 2 | `Anger` | 8 | 1 | 9 |
+| 3 | `Compassion` | 33 | 5 | 38 |
+| 4 | `Contempt` | 16 | 1 | 17 |
+| 5 | `Disappointment` | 42 | 8 | 50 |
+| 6 | `Disgust` | 33 | 10 | 43 |
+| 7 | `Fear` | 8 | 1 | 9 |
+| 8 | `Guilt` | 13 | 6 | 19 |
+| 9 | `Hate` | 10 | 2 | 12 |
+| 10 | `Interest` | 9 | 2 | 11 |
+| 11 | `Joy` | 128 | 35 | 163 |
+| 12 | `Pleasure` | 36 | 8 | 44 |
+| 13 | `Love` | 40 | 10 | 50 |
+| 14 | `Contentment` | 41 | 12 | 53 |
+| 15 | `Pride` | 27 | 13 | 40 |
+| 16 | `Regret` | 12 | 8 | 20 |
+| 17 | `Relief` | 24 | 2 | 26 |
+| 18 | `Sadness` | 67 | 18 | 85 |
+| 19 | `Shame` | 19 | 2 | 21 |
+
+Codebook: `label_taxonomy.json`.
+
+## Features
+
+| Field | Type | Description |
+|-------|------|-------------|
+| `id` | string | Example id |
+| `title` | string | Poem title |
+| `author` | string | Poet |
+| `poem` | string | Full poem body |
+| `labels` | list[int64] | Affect class indices |
+| `label_names` | list[string] | Canonical affect names |
+| `scores` | list[float64] | Mean MTurk intensities (length 20, taxonomy order) |
+| `n_annotators` | int64 | Number of MTurk annotations aggregated |
+
+## Construction method
+
+1. Load MTurk `combined.csv`; group by `(title, Author)`; average the 20 affect columns.
+2. Resolve poem text from `poems/` via normalized filename matching.
+3. Binarize with within-poem \(z \ge 1.0\) + top-1.
+4. Stratified train/test split by primary affect.
+
+## Citation
+
+```bibtex
+@article{khan_hopkins_gunes_2021,
+  title={Multi-dimensional Affect in Poetry (POCA) Dataset: Acquisition, Annotation and Baseline Results},
+  url={https://www.repository.cam.ac.uk/handle/1810/326293},
+  DOI={10.17863/CAM.73749},
+  publisher={IEEE},
+  author={Khan, Akbir and Hopkins, Jack and Gunes, Hatice},
+  year={2021}
+}
+```
+
+Also: https://doi.org/10.1109/ACII52823.2021.9597451
+
+## License
+
+Follow upstream POCA / Cambridge repository terms (research use; rights reserved by authors/publisher unless otherwise noted).

data/test-00000-of-00001.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:2b2738e9ba52b44e6baf9b56e53ac4212ac3735e1221b562d3534a45303206ce
+size 52390

data/train-00000-of-00001.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:cae687d6850324e6b18adbbe4caf3c02f56f2dcc2e7ecfaa3881dac4fc0e6194
+size 226618

dataset_infos.yaml

@@ -0,0 +1,40 @@
+configs:
+- config_name: default
+  data_files:
+  - path: data/train-*.parquet
+    split: train
+  - path: data/test-*.parquet
+    split: test
+  default: true
+dataset_info:
+  configs:
+  - config_name: default
+    dataset_size: 279008
+    download_size: 279008
+    features:
+    - dtype: string
+      name: id
+    - dtype: string
+      name: title
+    - dtype: string
+      name: author
+    - dtype: string
+      name: poem
+    - sequence:
+        dtype: int64
+      name: labels
+    - sequence:
+        dtype: string
+      name: label_names
+    - sequence:
+        dtype: float64
+      name: scores
+    - dtype: int64
+      name: n_annotators
+    splits:
+    - name: train
+      num_bytes: 226618
+      num_examples: 227
+    - name: test
+      num_bytes: 52390
+      num_examples: 61

label_taxonomy.json

@@ -0,0 +1,158 @@
+{
+  "n_classes": 20,
+  "labels": [
+    {
+      "id": 0,
+      "name": "Admiration"
+    },
+    {
+      "id": 1,
+      "name": "Amusement"
+    },
+    {
+      "id": 2,
+      "name": "Anger"
+    },
+    {
+      "id": 3,
+      "name": "Compassion"
+    },
+    {
+      "id": 4,
+      "name": "Contempt"
+    },
+    {
+      "id": 5,
+      "name": "Disappointment"
+    },
+    {
+      "id": 6,
+      "name": "Disgust"
+    },
+    {
+      "id": 7,
+      "name": "Fear"
+    },
+    {
+      "id": 8,
+      "name": "Guilt"
+    },
+    {
+      "id": 9,
+      "name": "Hate"
+    },
+    {
+      "id": 10,
+      "name": "Interest"
+    },
+    {
+      "id": 11,
+      "name": "Joy"
+    },
+    {
+      "id": 12,
+      "name": "Pleasure"
+    },
+    {
+      "id": 13,
+      "name": "Love"
+    },
+    {
+      "id": 14,
+      "name": "Contentment"
+    },
+    {
+      "id": 15,
+      "name": "Pride"
+    },
+    {
+      "id": 16,
+      "name": "Regret"
+    },
+    {
+      "id": 17,
+      "name": "Relief"
+    },
+    {
+      "id": 18,
+      "name": "Sadness"
+    },
+    {
+      "id": 19,
+      "name": "Shame"
+    }
+  ],
+  "binarization": {
+    "rule": "within-poem z>=1.0 + always include top-1",
+    "score_aggregation": "mean over MTurk annotators",
+    "score_scale": "0-10"
+  },
+  "counts": {
+    "train": {
+      "Disappointment": 42,
+      "Pride": 27,
+      "Contentment": 41,
+      "Pleasure": 36,
+      "Love": 40,
+      "Amusement": 95,
+      "Compassion": 33,
+      "Sadness": 67,
+      "Admiration": 56,
+      "Joy": 128,
+      "Relief": 24,
+      "Disgust": 33,
+      "Contempt": 16,
+      "Regret": 12,
+      "Anger": 8,
+      "Hate": 10,
+      "Interest": 9,
+      "Shame": 19,
+      "Guilt": 13,
+      "Fear": 8
+    },
+    "test": {
+      "Sadness": 18,
+      "Amusement": 28,
+      "Joy": 35,
+      "Disappointment": 8,
+      "Love": 10,
+      "Pleasure": 8,
+      "Contentment": 12,
+      "Pride": 13,
+      "Fear": 1,
+      "Guilt": 6,
+      "Disgust": 10,
+      "Anger": 1,
+      "Hate": 2,
+      "Regret": 8,
+      "Admiration": 11,
+      "Relief": 2,
+      "Compassion": 5,
+      "Interest": 2,
+      "Shame": 2,
+      "Contempt": 1
+    },
+    "all": {
+      "Amusement": 123,
+      "Anger": 9,
+      "Disgust": 43,
+      "Guilt": 19,
+      "Contempt": 17,
+      "Relief": 26,
+      "Pleasure": 44,
+      "Regret": 20,
+      "Joy": 163,
+      "Love": 50,
+      "Sadness": 85,
+      "Disappointment": 50,
+      "Fear": 9,
+      "Compassion": 38,
+      "Admiration": 67,
+      "Pride": 40,
+      "Contentment": 53,
+      "Hate": 12,
+      "Shame": 21,
+      "Interest": 11
+    }
+  }
+}