Update README.md

README.md

@@ -15,6 +15,9 @@ This repository contains parsed datasets used in the RuleFollower project.
 - **Hatecot**
 - **Implicit Hate**
 - **Yelp Reviews**
+- **Article Bias Prediction**
+- **Politeness Wiki**
+- **Politeness Stack**
 
 Each folder contains a `data.csv` file with the parsed annotations. Each dataset is capped at 5k samples (full dataset used if <5k). 
 
@@ -128,4 +131,31 @@ Each data file includes standardized columns:
 - **Dataset**: [Data](https://www.yelp.com/dataset)
 - **Annotation goal**:
   - Sentiment Task: Classify the overall evaluation expressed in a Yelp restaurant review.
+- **Ground truth**: Provided
+
+---
+
+### Article Bias Prediction
+- **Text content**: News articles (A set of articles from media sources covering the United States of America. Data was scraped from https://www.allsides.com/.)
+- **Source**: [Baly et al. (2020)](https://aclanthology.org/2020.emnlp-main.404/)
+- **Dataset**: [Data](https://github.com/ramybaly/Article-Bias-Prediction)
+- **Annotation goal**: Classify the political bias expressed in a news article based on its content.Labels: `0`(left), `1`(center), `2`(right)
+- **Ground truth**: Provided
+
+---
+
+### Politeness Wiki
+- **Text content**: Requests from Wikipedia editor’s on user talk pages.
+- **Source**: [Danescu-Niculescu-Mizil et al. (2013)](https://aclanthology.org/P13-1025.pdf)
+- **Dataset**: [Data](https://convokit.cornell.edu/documentation/wiki_politeness.html)
+- **Annotation goal**: Classify the level of politeness in the text. Labels: `1`(polite), `0`(neutral), `-1`(impolite).
+- **Ground truth**: Provided
+
+---
+
+### Politeness Wiki
+- **Text content**: Requests from the StackExchange question-answering communities. These are often users commenting on existing posts requesting further information or proposing edits.
+- **Source**: [Danescu-Niculescu-Mizil et al. (2013)](https://aclanthology.org/P13-1025.pdf)
+- **Dataset**: [Data](https://convokit.cornell.edu/documentation/stack_politeness.html)
+- **Annotation goal**: Classify the level of politeness of the text. Labels: `1`(polite), `0`(neutral), `-1`(impolite).
 - **Ground truth**: Provided