Crawled Use Cases

The "crawled" filter in Webz.io’s open web API allows users to filter posts based on the time they were crawled, using a timestamp in milliseconds to specify a date and time. This filter is useful for refining search results to include only posts crawled before or after a certain moment, regardless of the original publish date. Here’s how the crawled filter can be applied across different scenarios:

1. Real-Time Data Monitoring: By setting the crawled filter to a recent timestamp, users can focus on newly crawled posts, enabling them to monitor the latest data as it’s being collected. This is particularly valuable for users needing up-to-date information, such as breaking news, crisis management, or trend monitoring.
2. Historical Data Analysis: For users conducting research on past events, the crawled filter can be set to a specific time frame to retrieve only posts that were collected during or right after an event. This allows researchers to analyze news as it was being reported in real-time, providing valuable context and insights into how a story unfolded.
3. Ensuring Data Freshness: Businesses and analysts who prioritize recent data for market analysis or competitor monitoring can use this filter to limit results to articles crawled after a specific date. This ensures they are working with the freshest data available without outdated information.
4. Studying Data Collection Trends: Researchers can use the crawled filter to analyze the frequency and volume of data collected over time. By comparing different crawling periods, they can gain insights into the flow of information, peak coverage times, or shifts in media attention across specific topics or industries.
5. Customizing News Feeds for Aggregators: News platforms and content aggregators can use the crawled filter to ensure that they display only recently crawled posts. This keeps their content current and engaging for audiences, especially when timeliness is a priority.
6. Focused Data Collection for Training Models: AI and data scientists building language models may want to train on content crawled within a specific timeframe to reflect current language usage, topics, and trends. Using the crawled filter, they can curate a dataset that aligns with the desired period.
7. Efficient Retrospective Analysis: Analysts can use the crawled filter to look back at data crawled during specific periods, such as the beginning or peak of a news cycle. This helps them study initial reporting patterns, public interest, or sentiment trends during key moments.

The crawled filter provides precise control over when content was collected, making it ideal for users who need timely or historical data, recent updates, or curated datasets based on specific crawling periods. It helps ensure data relevance, timeliness, and consistency for various applications, from real-time monitoring to retrospective analysis.

Example query: crawled:>now-1h
Example query: crawled:>1490865388000
Will return posts crawled after the mentioned time stamp.