Update README.md

README.md

@@ -1,47 +1,67 @@
 ---
-dataset_info:
-  features:
-  - name: text
-    dtype: string
-  - name: article_id
-    dtype: string
-  - name: annotators
-    sequence: string
-  - name: HATEFUL
-    sequence: string
-  - name: CALLS
-    sequence: string
-  - name: WOMEN
-    sequence: string
-  - name: LGBTI
-    sequence: string
-  - name: RACISM
-    sequence: string
-  - name: CLASS
-    sequence: string
-  - name: POLITICS
-    sequence: string
-  - name: DISABLED
-    sequence: string
-  - name: APPEARANCE
-    sequence: string
-  - name: CRIMINAL
-    sequence: string
-  - name: tweet_id
-    dtype: string
-  - name: user_id
-    dtype: string
-  - name: id
-    dtype: int64
-  splits:
-  - name: train
-    num_bytes: 14669129
-    num_examples: 56869
-  download_size: 5847160
-  dataset_size: 14669129
-configs:
-- config_name: default
-  data_files:
-  - split: train
-    path: data/train-*
+language:
+- es
+pretty_name: contextualized_hate_speech
+task_categories:
+- text-classification
+tags:
+- hate_speech
+size_categories:
+- 10K<n<100K
 ---
+# Contextualized Hate Speech: A dataset of comments in news outlets on Twitter
+
+## Dataset Description
+
+- **Homepage:** 
+- **Repository:** 
+- **Paper**: ["Assessing the impact of contextual information in hate speech detection"](https://arxiv.org/abs/2210.00465), Juan Manuel Pérez, Franco Luque, Demian Zayat, Martín Kondratzky, Agustín Moro, Pablo Serrati, Joaquín Zajac, Paula Miguel, Natalia Debandi, Agustín Gravano, Viviana Cotik
+- **Point of Contact**: jmperez (at) dc uba ar
+
+### Dataset Summary
+![Graphical representation of the dataset](Dataset%20graph.png)
+This dataset is a collection of tweets that were posted in response to news articles from five specific Argentinean news outlets: Clarín, Infobae, La Nación, Perfil and Crónica, during the COVID-19 pandemic. The comments were analyzed for hate speech across eight different characteristics: against women, racist content, class hatred, against LGBTQ+ individuals, against physical appearance, against people with disabilities, against criminals, and for political reasons. All the data is in Spanish.
+
+Each comments is labeled with the following variables
+
+
+
+| Label      | Description                                                             |
+| :--------- | :---------------------------------------------------------------------- |
+| HATEFUL    | Contains hate speech (HS)?                                              |
+| CALLS      | If it is hateful, is this message calling to (possibly violent) action? |
+| WOMEN      | Is this against women?                                                  |
+| LGBTI      | Is this against LGBTI people?                                           |
+| RACISM     | Is this a racist message?                                               |
+| CLASS      | Is this a classist message?                                             |
+| POLITICS   | Is this HS due to political ideology?                                   |
+| DISABLED   | Is this HS against disabled people?                                     |
+| APPEARANCE | Is this HS against people due to their appearance? (e.g. fatshaming)    |
+| CRIMINAL   | Is this HS against criminals or people in conflict with law?            |
+
+
+
+There is an extra label `CALLS`, which represents whether a comment is a call to violent action or not.
+
+For each comment, we have a list of annotators who marked the comment first as HATEFUL, and then the selected categories (one or more).
+
+An aggregated version of the dataset can be found at [piuba-bigdata/contextualized_hate_speech](https://huggingface.co/datasets/piuba-bigdata/contextualized_hate_speech/)
+### Citation Information
+
+```bibtex
+@article{perez2022contextual,
+  author  = {Pérez, Juan Manuel and Luque, Franco M. and Zayat, Demian and Kondratzky, Martín and Moro, Agustín and Serrati, Pablo Santiago and Zajac, Joaquín and Miguel, Paula and Debandi, Natalia and Gravano, Agustín and Cotik, Viviana},
+  journal = {IEEE Access},
+  title   = {Assessing the Impact of Contextual Information in Hate Speech Detection},
+  year    = {2023},
+  volume  = {11},
+  number  = {},
+  pages   = {30575-30590},
+  doi     = {10.1109/ACCESS.2023.3258973}
+}
+
+```
+
+### Contributions
+
+[More Information Needed]