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README.md

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+# Dataset Card for Dataset Name
+
+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. 
+
+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
+and comment text. 
+
+In this version, the data is called directly from the API, which can result in slow load times.
+If the user wants to simply load a pre-downloaded dataset, 
+reference https://huggingface.co/datasets/ro-h/regulatory_comments.
+
+## Dataset Details
+
+### Dataset Description and Structure
+
+This dataset will call the API to individually gather docket and comment information; data collection will stop when 
+all dockets with opioid-related information have been gathered, or when the API hits a rate-limit. The government 
+API limit is 1000 calls per hour. Since each comment's text requires an individual call and there will be ~10 comments collected per docket, 
+only around 100 dockets can be collected without extending the limit. Furthermore, since some dockets don't have comment data and 
+thus will not be included, it is realistic to expect approximatley 60-70 dockets collected. 
+
+If a larger set of dockets are required, consider requesting a rate-unlimited API key. For more details, visit 
+[https://open.gsa.gov/api/regulationsgov/].
+
+The following information is included in this dataset: 
+
+**Docket Metadata**
+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.
+context (str): The date when the docket was last modified on Regulations.gov.
+purpose (str): Whether the docket was rulemaking, non-rulemaking, or other.
+keywords (list): A string of keywords, as determined by Regulations.gov.
+
+**Comment Metadata**
+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_date (str): The date when the comment was posted on Regulations.gov. This is important for understanding the timeline of public engagement.
+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. 
+
+- **Curated by:** Ro Huang
+
+### Dataset Sources
+
+- **Repository:** [https://huggingface.co/datasets/ro-h/regulatory_comments_api]
+- **Original Website:** [https://www.regulations.gov/]
+- **API Website:** [https://open.gsa.gov/api/regulationsgov/]
+
+## Uses
+
+This dataset may be used by researchers or policy-stakeholders curious about the influence of 
+public comments on regulation development. For example, sentiment analysis may be run on 
+comment text; alternatively, simple descriptive analysis on the comment length and agency regulation
+may prove interesting.
+
+## Dataset Creation
+
+### Curation Rationale
+
+After a law is passed, it may require specific details or guidelines to be practically enforceable or operable. 
+Federal agencies and the Executive branch engage in rulemaking, which specify the practical ways that legislation 
+can get turned into reality. Then, they will open a Public Comment period in which they will receive comments, 
+suggestions, and questions on the regulations they proposed. After taking in the feedback, the agency will modify their 
+regulation and post a final rule.
+
+As an example, imagine that the legislative branch of the government passes a bill to increase the number of hospitals 
+nationwide. While the Congressman drafting the bill may have provided some general guidelines (e.g., there should be at 
+least one hospital in a zip code), there is oftentimes ambiguity on how the bill’s goals should be achieved.
+The Department of Health and Human Services is tasked with implementing this new law, given its relevance to national 
+healthcare infrastructure. The agency would draft and publish a set of proposed rules, which might include criteria for 
+where new hospitals can be built, standards for hospital facilities, and the process for applying for federal funding. 
+During the Public Comment period, healthcare providers, local governments, and the public can provide feedback or express
+concerns about the proposed rules. The agency will then read through these public comments, and modify their regulation 
+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, 
+an issue that a diversity of stakeholders have investment in. 
+
+#### Data Collection and Processing
+
+**Filtering Methods:**
+For each docket, we retrieve relevant metadata such as docket ID, 
+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.
+
+**Data Normalization:**
+The collected data is normalized into a structured format. Each docket and 
+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.
+
+**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. 
+Python: The entire data collection and processing script is written in Python.
+
+**Error Handling:**
+In the event of a failed API request (indicated by a non-200 HTTP response status), 
+the data collection process for the current docket is halted, and the process moves to the next docket.