Datasets:

Khubaib01
/

RUEmoCorp

@@ -104,6 +104,7 @@ This dataset is part of a growing research programme on Roman Urdu affective com
 ## 3. Dataset Statistics
 ### 3.1 Size and Format
 | Property | Value |
@@ -130,6 +131,56 @@ This dataset is part of a growing research programme on Roman Urdu affective com
 > The dataset was constructed with approximate class balance to ensure unbiased classifier training.
 ### 3.3 IAA Validation Subset
 A stratified random sample of **700 instances** (100 per class) was independently re-annotated by all four annotators for the IAA study. Results are reported in Section 4.
@@ -339,7 +390,7 @@ print(result)
 | roman-urdu-emotion-xlmr-v2 | Emotion classifier v2 (current best) | [HuggingFace](https://huggingface.co/Khubaib01/roman-urdu-emotion-xlmr-v2) |
 | Paper | In-progess | in-progress |
 | Harvard Dataverse | Archival deposit | under-review |
-| RomanUrdu-NLP-Emotion-Corpus-134K | 134K model-labeled emotion corpus | *Forthcoming* |
 ---
@@ -492,13 +543,15 @@ Yes. Versioned releases on both HuggingFace and Harvard Dataverse.
 If you use this dataset in your research, please cite:
 ```bibtex
-@misc{muhammad_khubaib_ahmad_2026,
-	author       = { Muhammad Khubaib Ahmad and Khadija Faisal },
-	title        = { RUEmoCorp (Revision 13f5266) },
-	year         = 2026,
-	url          = { https://huggingface.co/datasets/Khubaib01/RUEmoCorp },
-	doi          = { 10.57967/hf/8711 },
-	publisher    = { Hugging Face }
 }
 ```

 ## 3. Dataset Statistics
+## RUEmoCorp (28k) training
 ### 3.1 Size and Format
 | Property | Value |
 > The dataset was constructed with approximate class balance to ensure unbiased classifier training.
+## Dataset Statistics — `RUEmoCorp-silver`
+> RUEmoCorp is annotated by the Khubaib01/roman-urdu-emotion-xlmr-v2
+### Overview
+| Property | Value |
+|----------|-------|
+| Total utterances | 134,053 |
+| Annotation method | Automated — `roman-urdu-emotion-xlmr-v2` |
+| Confidence threshold | ≥ 0.75 (softmax probability) |
+| Mean confidence | 0.8039 |
+| Median confidence | 0.8733 |
+| Mean prediction entropy | 0.7623 |
+| Low-confidence rows (< 0.75) | 10,109 (7.54%) |
+| Fallback / unresolved rows | 0 (0.00%) |
+The high median confidence (0.8733) indicates that the majority of retained predictions are well above the retention threshold, with low-confidence rows constituting only 7.54% of the corpus. Zero fallback rows confirm complete model coverage across all retained utterances.
+---
+### Class Distribution (with 95% Wilson Confidence Intervals)
+| Emotion | Count | % | CI Lower | CI Upper |
+|---------|------:|--:|:--------:|:--------:|
+| joy | 28,389 | 21.18% | 0.2096 | 0.2140 |
+| none | 28,167 | 21.01% | 0.2079 | 0.2123 |
+| disgust | 25,959 | 19.36% | 0.1915 | 0.1958 |
+| sadness | 22,570 | 16.84% | 0.1664 | 0.1704 |
+| anger | 18,275 | 13.63% | 0.1345 | 0.1382 |
+| fear | 6,613 | 4.93% | 0.0482 | 0.0505 |
+| surprise | 4,080 | 3.04% | 0.0295 | 0.0314 |
+> ⚠️ The distribution is **naturally imbalanced**, reflecting the organic frequency of emotional expression in scraped social media and WhatsApp data. `joy` and `none` together account for ~42% of the corpus. `fear` and `surprise` are the least frequent classes (combined ~8%). Users should apply class reweighting or stratified sampling before using this corpus as a primary training source.
+---
+### Per-Class Confidence Statistics
+| Emotion | Mean Conf. | Std | Median Conf. | Min | Max |
+|---------|:----------:|:---:|:------------:|:---:|:---:|
+| anger | 0.8175 | 0.1292 | 0.8778 | 0.2291 | 0.9105 |
+| disgust | 0.7819 | 0.1499 | 0.8630 | 0.1875 | 0.9142 |
+| fear | 0.7545 | 0.1842 | 0.8484 | 0.1900 | 0.9320 |
+| joy | 0.8476 | 0.1244 | 0.9037 | 0.2336 | 0.9290 |
+| none | 0.8155 | 0.1361 | 0.8804 | 0.2207 | 0.9193 |
+| sadness | 0.7696 | 0.1510 | 0.8488 | 0.2147 | 0.9068 |
+| surprise | 0.7699 | 0.1755 | 0.8637 | 0.2195 | 0.9294 |
+`joy` and `anger` record the highest mean confidence (0.8476 and 0.8175 respectively), consistent with their strong per-class F1 scores on the human-annotated gold set. `fear` and `surprise` record the lowest mean confidence and highest standard deviation, reflecting their lower corpus frequency and greater lexical ambiguity in informal Roman Urdu — also the classes with the widest Wilson CI bounds in the distribution table above. All per-class median confidence values exceed 0.84, indicating that the central tendency of predictions is substantially above the 0.75 retention threshold across all seven categories.
 ### 3.3 IAA Validation Subset
 A stratified random sample of **700 instances** (100 per class) was independently re-annotated by all four annotators for the IAA study. Results are reported in Section 4.
 | roman-urdu-emotion-xlmr-v2 | Emotion classifier v2 (current best) | [HuggingFace](https://huggingface.co/Khubaib01/roman-urdu-emotion-xlmr-v2) |
 | Paper | In-progess | in-progress |
 | Harvard Dataverse | Archival deposit | under-review |
+| RomanUrdu-NLP-Emotion-Corpus-134K | 134K model-labeled emotion corpus | [HuggingFace](https://huggingface.co/Khubaib01/RUEmoCorp) |
 ---
 If you use this dataset in your research, please cite:
 ```bibtex
+@data{DVN/BPWHOZ_2026,
+author = {Ahmad, Muhammad Khubaib Ahmad and Khadija Faisal},
+publisher = {Harvard Dataverse},
+title = {{RUEmoCorp}},
+UNF = {UNF:6:h03jo4SJGEAKuZCik1R/Bw==},
+year = {2026},
+version = {V1},
+doi = {10.7910/DVN/BPWHOZ},
+url = {https://doi.org/10.7910/DVN/BPWHOZ}
 }
 ```