Event Tagging System
Prediction markets cover many different topics, timelines, and event types. An event tagging system assigns standardized tags to each event, such as category, region, asset type, or event theme. These tags make large datasets easier to work with. Analysts can filter, group, and compare events without relying on manual interpretation of titles or descriptions.
Tagging also improves consistency across markets. When similar events share the same tags, their prediction markets data becomes easier to aggregate and analyze together. Over time, tagging systems support deeper insights. They enable trend analysis across event types and help identify where forecasting performance is strong or weak.
For analysts, an event tagging system provides essential structure. It turns unorganized markets into a searchable, analyzable dataset.
Why It Matters
Without tagging, prediction markets data becomes difficult to scale. Event tagging systems make analysis faster, clearer, and more reliable.
What is an event tagging system in prediction markets?
In prediction markets, an event tagging system assigns standardized labels to each market event. These labels describe what the event is about and how it should be grouped. This helps analysts organize and query data efficiently. It reduces ambiguity in large datasets.
How does an event tagging system improve prediction markets data analysis?
Event tagging systems allow analysts to filter and compare prediction markets data across similar events. They make it easier to study patterns by category, region, or topic. This supports cross-event analysis and performance evaluation. Tagging improves both speed and accuracy of analysis.
Why are event tagging systems important for prediction markets APIs?
Prediction markets APIs often expose hundreds or thousands of events. Event tagging systems make API data usable by enabling structured filtering and aggregation. Analysts can request or process subsets of markets programmatically. APIs combined with tagging support scalable and automated workflows.
Real-World Example
On Kalshi, markets may be tagged by economic indicator type or release schedule. These tags allow analysts to study how different categories of events behave over time.
Event Tagging System and FinFeedAPI
FinFeedAPI’s Prediction Markets API provides event metadata that can be used to build event tagging systems. Analysts can apply and manage tags to organize prediction markets data across categories and timeframes. This supports structured analysis, filtering, and modeling. The API enables consistent tagging workflows across prediction markets.