Update README.md

README.md

@@ -1,18 +1,22 @@
 ---
-license: apache-2.0
+license: cc-by-4.0
 language:
 - ur
+- en
 tags:
 - roman-urdu
-- emotion-recognition
-- sentiment-analysis
+- emotion-classification
+- text-classification
+- ekman
+- nlp
 - low-resource-nlp
 - affective-computing
-- social-media-nlp
-- urdu
-- nlp
-- text-classification
-pretty_name: Roman Urdu Emotion Corpus (RUEC-28K)
+- social-media
+- urdu-nlp
+- mental-health
+- whatsapp
+- inter-annotator-agreement
+pretty_name: RUEmoCorp — Roman Urdu Emotion Corpus
 size_categories:
 - 10K<n<100K
 task_categories:
@@ -21,12 +25,22 @@ task_ids:
 - multi-class-classification
 annotations_creators:
 - expert-generated
+- machine-generated
 language_creators:
 - found
 multilinguality:
 - monolingual
 source_datasets:
 - Khubaib01/RomanUrdu-NLP-Sentiment-Corpus
+configs:
+- config_name: ruemocorp-annotated
+  data_files:
+    - split: train
+      path: RUEmoCorpus.csv
+- config_name: ruemocorp-silver
+  data_files:
+    - split: train
+      path: RUEmoCorp_134k_labeled/RUEmoCorp_134k_labeled.csv
 ---
 
 # Roman Urdu Emotion Corpus (RUEC-28K)
@@ -61,14 +75,15 @@ source_datasets:
 
 ---
 
-## 1. Dataset Overview
+## Dataset Overview
 
-**RUEC-28K** (Roman Urdu Emotion Corpus) is a manually curated, expert-annotated dataset of **28,000 Roman Urdu social media texts** labeled across **7 emotion categories**: *Anger, Disgust, Fear, Happy, Neutral, Sad,* and *Surprise*. It is the training corpus behind [`roman-urdu-emotion-xlmr-v2`](https://huggingface.co/Khubaib01/roman-urdu-emotion-xlmr-v2), the highest-performing open-source Roman Urdu emotion classifier currently available.
+**RUEmoCorp** (Roman Urdu Emotion Corpus) is a large-scale, manually curated, expert-annotated dataset of Roman Urdu social media and conversational texts labeled across **7 emotion categories**: *joy, anger, sadness, fear, disgust, surprise,* and *none*. It is the training corpus behind [`roman-urdu-emotion-xlmr-v2`](https://huggingface.co/Khubaib01/roman-urdu-emotion-xlmr-v2) — the highest-accuracy open-source emotion classifier for Roman Urdu, achieving **Macro F1 = 0.9896**.
 
-The dataset was derived from the parent [RomanUrdu-NLP-Sentiment-Corpus (134K)](https://huggingface.co/datasets/Khubaib01/RomanUrdu-NLP-Sentiment-Corpus) and underwent a rigorous multi-phase blind annotation process by a four-person expert team. An Inter-Annotator Agreement (IAA) study on a 700-sample stratified subset yields **Fleiss' κ = 0.659** and **Mean Pairwise Cohen's κ = 0.660**, indicating *substantial agreement* — a strong benchmark for a 7-class affective label task in a low-resource, orthographically irregular language.
+Data was collected from Pakistani social media platforms and WhatsApp conversations and underwent a rigorous multi-phase annotation process by four expert annotators recruited from three independent Pakistani universities. An inter-annotator agreement (IAA) study on a 700-sample benchmark yields **Fleiss' κ = 0.6588** and **Mean Pairwise Cohen's κ = 0.6597**, indicating *substantial agreement* (Landis & Koch, 1977) — a strong result for a 7-class affective labeling task in a low-resource, orthographically irregular language.
 
-**This dataset fills a documented gap**: prior to this release, no large-scale, openly accessible, IAA-validated emotion dataset existed for Roman Urdu, despite Roman Urdu being the dominant digital writing mode for over 230 million Urdu speakers.
+The emotion taxonomy adopts Ekman's six universal basic emotions augmented with a *none* class for emotionally neutral utterances — a deliberate design choice absent from prior Roman Urdu emotion work, which has used only four or six categories. Omitting a neutral class forces classifiers to assign emotional labels to neutral text, inflating false positive rates in deployed systems.
 
+**This dataset fills a documented gap**: prior to this release, no large-scale, openly accessible, IAA-validated emotion corpus existed for Roman Urdu, despite Roman Urdu being the dominant digital writing mode for over 230 million Urdu speakers worldwide. RUEmoCorp is permanently archived on Harvard Dataverse (doi:[10.7910/DVN/BPWHOZ](https://doi.org/10.7910/DVN/BPWHOZ)) and released under CC BY 4.0.
 ---
 
 ## 2. Background and Motivation