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