Update README.md

README.md

@@ -15,7 +15,7 @@ task_categories:
 
 United States governmental agencies often make proposed regulations open to the public for comment. 
 Proposed regulations are organized into "dockets". This dataset will use Regulation.gov public API 
-to aggregate and clean public comments for dockets that mention opioid use. 
+to aggregate and clean public comments for dockets that mention substance use. 
 
 Each example will consist of one docket, and include metadata such as docket id, docket title, etc. 
 Each docket entry will also include information about the top 10 comments, including comment metadata
@@ -28,6 +28,9 @@ The code used to call the api can be found in api_call.py.
 If the user wants to call from the API
 directly, reference [https://huggingface.co/datasets/ro-h/regulatory_comments_api].
 
+For an example of how to use this dataset, 
+reference [https://colab.research.google.com/drive/1AiFznbHaDVszcmXYS3Ht5QLov2bvfQFX?usp=sharing].
+
 ## Dataset Details
 
 ### Dataset Description and Structure
@@ -45,13 +48,18 @@ The following information is included in this dataset:
 
 id (int): A unique numerical identifier assigned to each regulatory docket.
 
-title (str): The official title or name of the regulatory docket. This title typically summarizes the main issue or area of regulation covered by the docket.
+agency (str): The abbreviation for the agency posting the regulatory docket (e.g., "FDA")
+
+title (str): The official title or name of the regulatory docket. This title typically summarizes the main issue or 
+area of regulation covered by the docket.
+
+update_date (str): The date when the docket was last modified on Regulations.gov.
 
-context (str): The date when the docket was last modified on Regulations.gov.
+update_time (str): The time when the docket was last modified on Regulations.gov.
 
 purpose (str): Whether the docket was rulemaking, non-rulemaking, or other.
 
-keywords (list(str)): A list of string keywords, as determined by Regulations.gov.
+keywords (list): A string of keywords, as determined by Regulations.gov.
 
 **Comment Metadata**
 
@@ -59,21 +67,24 @@ Note that huggingface converts lists of dictionaries to dictionaries of lists.
 
 comment_id (int): A unique numerical identifier for each public comment submitted on the docket.
 
-comment_title (str): The title or subject line of the individual public comment.
+comment_url (str): A URL or web link to the specific comment or docket on Regulations.gov. This allows direct access 
+to the original document or page for replicability purposes.
 
-comment_url (str): A URL or web link to the specific comment or docket on Regulations.gov. This allows direct access to the original document or page for replicability purposes.
+comment_date (str): The date when the comment was posted on Regulations.gov. This is important for understanding the 
+timeline of public engagement.
 
-comment_date (str): The date when the comment was posted on Regulations.gov. This is important for understanding the timeline of public engagement.
+comment_time (str): The time when the comment was posted on Regulations.gov. 
 
-commenter_fname (str): The first name of the individual or entity that submitted the comment. This could be a person, organization, business, or government entity.
+commenter_fname (str): The first name of the individual or entity that submitted the comment. This could be a person, 
+organization, business, or government entity.
 
 commenter_lname (str): The last name of the individual or entity that submitted the comment. 
 
 comment_length (int): The length of the comment in terms of the number of characters (spaces included)
 
 **Comment Content**
-text (str): The actual text of the comment submitted. This is the primary content for analysis, containing the commenter's views, arguments, and feedback on the regulatory matter. 
-
+text (str): The actual text of the comment submitted. This is the primary content for analysis, containing the 
+commenter's views, arguments, and feedback on the regulatory matter. 
 
 ### Dataset Limitations
 
@@ -119,7 +130,7 @@ accordingly.
 
 While this is a vital part of the United States regulatory process, there is little understanding of how agencies approach
 public comments and modify their proposed regulations. Further, the data extracted from the API is often unclean and difficult
-to navigate. This dataset seeks to offer some clarity through aggregating comments related to Opioid Use Disorders, 
+to navigate. This dataset seeks to offer some clarity through aggregating comments related to substance use, 
 an issue that a diversity of stakeholders have investment in. 
 
 
@@ -131,7 +142,8 @@ title, context, purpose, and keywords. Additionally, the top 10 comments
 for each docket are collected, including their metadata (comment ID, URL, date,
 title, commenter's first and last name) and the comment text itself. The process 
 focuses on the first page of 25 comments for each docket, and the top 10 comments 
-are selected based on their order of appearance in the API response.
+are selected based on their order of appearance in the API response. Dockets 
+with no comments are filtered out. 
 
 **Data Normalization:**
 The collected data is normalized into a structured format. Each docket and 
@@ -139,6 +151,10 @@ its associated comments are organized into a nested dictionary structure.
 This structure includes key information about the docket and a list of comments,
 each with its detailed metadata.
 
+**Data Cleaning:**
+HTML text tags are removed from comment text. However, the content of the comment remains 
+unedited, meaning any typos or grammatical errors in the original comment are preserved.
+
 **Tools and Libraries Used:**
 Requests Library: Used for making API calls to the Regulations.gov API to fetch dockets and comments data.
 Datasets Library from HuggingFace: Employed for defining and managing the dataset's structure and generation process.