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README.md

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+---
+language:
+- en
+tags:
+- reddit
+- law
+pretty_name: Legal Advice Reddit
+---
+
+# Dataset Card for Legal Advice Reddit Dataset
+
+## Dataset Description
+
+- **Paper: [Parameter-Efficient Legal Domain Adaptation](https://aclanthology.org/2022.nllp-1.10/)** 
+- **Point of Contact: [email protected]** 
+
+### Dataset Summary
+
+New dataset introduced in [Parameter-Efficient Legal Domain Adaptation](https://aclanthology.org/2022.nllp-1.10) (Li et al., NLLP 2022) from the Legal Advice Reddit community (known as "/r/legaldvice"), sourcing the Reddit posts from the Pushshift
+Reddit dataset. The dataset maps the text and title of each legal question posted into one of eleven classes, based on the original Reddit
+post's "flair" (i.e., tag). Questions are typically informal and use non-legal-specific language. Per the Legal Advice Reddit rules, posts 
+must be about actual personal circumstances or situations. We limit the number of labels to the top eleven classes and remove the other 
+samples from the dataset.
+
+### Citation Information
+```
+@inproceedings{li-etal-2022-parameter,
+    title = "Parameter-Efficient Legal Domain Adaptation",
+    author = "Li, Jonathan  and
+      Bhambhoria, Rohan  and
+      Zhu, Xiaodan",
+    booktitle = "Proceedings of the Natural Legal Language Processing Workshop 2022",
+    month = dec,
+    year = "2022",
+    address = "Abu Dhabi, United Arab Emirates (Hybrid)",
+    publisher = "Association for Computational Linguistics",
+    url = "https://aclanthology.org/2022.nllp-1.10",
+    pages = "119--129",
+}
+```