The Article Data Extractor API is designed to extract relevant information from articles or blogs by providing the URL of the desired webpage. It scrapes and retrieves data such as the article's title, text, published time, media links, and more. The API aims to save time by delivering structured data that can be easily filtered, queried, and stored for further use.

The Article Data Extractor API can extract various types of information from articles or blogs. This includes the article's title, main text content, published time, media links (such as images or videos embedded within the article), and potentially other metadata associated with the article.

The accuracy of data extraction depends on factors such as the structure and quality of the webpage, as well as the consistency of its layout and formatting. The API employs scraping techniques to retrieve information, and its accuracy may vary based on these factors. However, it is designed to provide reliable and relevant data from the provided article or blog URL.

No, at the moment batch requests are not supported. You will have to make one API call per article that you want to extract the data from.

The extracted data from the articles or blogs is typically returned in a structured format, such as JSON. This makes it easier to work with the data programmatically, as you can access specific fields and properties. The API organizes the extracted information in a structured manner, allowing you to filter, query, and store the data as per your requirements.

The API returns structured data from articles, including key fields such as the article's title, main content, published time, media links (images/videos), and metadata like tags and author names. This allows users to easily access and utilize relevant information.

The response data is organized in a JSON format, which includes an "error" field indicating success or failure, a "message" field for status updates, and a "data" object containing the extracted article details. This structure facilitates easy parsing and integration into applications.

Key fields in the response data include "url" (the article's link), "title" (the article's title), "description" (a summary of the content), "links" (media links), "image" (featured image), and "content" (the main text of the article). These fields provide comprehensive information for analysis.

The API can extract various information types, including the article's title, main text, publication date, author name, tags, and media links. This makes it suitable for content analysis, marketing research, and data organization.

Users can customize their requests by providing different article URLs to the API. Each URL will yield specific data based on the content of that article, allowing users to tailor their data extraction to their needs.

Typical use cases include content aggregation for news platforms, competitive analysis for marketing agencies, and research for academic purposes. Users can filter articles by author, tags, or publication dates for better organization.

Data accuracy is maintained through the API's scraping techniques, which are designed to extract relevant information from well-structured articles. However, accuracy may vary based on the webpage's layout and quality.

Users can utilize the returned data by integrating it into their applications for content management, analysis, or reporting. The structured JSON format allows for easy filtering, querying, and storage, enhancing data usability.

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