Machine-learning signal tracking US fiscal policy sentiment - measuring debt ceiling commentary, spending and tax debates, and market perception of government budget trajectory and sustainability.

The Fiscal Policy index is derived from AI-powered NLP analysis of thousands of online news sources, blogs, and financial commentary. Sentiment scores range from 0 (Deeply Negative) to 100 (Strongly Positive), where 50 represents neutral conditions. Awareness scores capture the volume and breadth of coverage for this topic across the media landscape.

The underlying data pipeline runs once per day. However, the gauge and score displayed on this page reflect a processed snapshot that may be 3–24 hours behind real-time, depending on the topic's update cadence and how quickly new data clears the processing pipeline. The exact timestamp of the data shown is visible in the gauge footer - hover the info icon to see it in your local time.

The gauge reflects a processed data snapshot, not a live feed. Depending on the topic, displayed values can be 3–24 hours behind real-time - fast-moving topics (crypto, equities) update more frequently, while slower-cycle topics (macro, real estate, geopolitics) may have a longer lag. The precise data timestamp is always visible in the gauge footer: hover the info icon to see it in your local time.

Sentiment uses natural language processing to analyze and quantify investors' opinions, which is different from traditional indicators like volatility (VIX), volume, or price trends. This gives you an edge over others who rely solely on price-based data.

The gauges show the latest indicator percentiles for the last two quarters. Values above 50 mean an upward trend, while below 50 means a downward trend. A reading above 70% signals greed, and below 30% signals fear. When price and sentiment trends diverge, it's a strong sign the trend will continue.

Besides sentiment, we also provide a measurement of awareness - an indicator of media activity expressed as a ratio of topic-dedicated data compared to the total. Values over 50 indicate an increasing media trend and growing investors' interest; less than 50 signals decreasing attention.

Sentiment analysis is a way to determine whether a piece of text is positive, negative, or neutral. It helps understand how people feel about a topic or product, which is very important for investment, revenue management, and gauging public opinion. It adds important data points to the decision process and is valuable input for many statistical and AI models.

Raw signals are gathered from proprietary sources covering over 50,000 outlets and ingested every 15 minutes. Processed gauge readings are derived from these signals but are displayed with a delay of 3–24 hours depending on the topic - the exact data timestamp is always shown in the gauge footer. The platform includes 5 years of history, supports 72 languages, and processes over 1 million unique entries daily. Adalytica maintains over 99.5% uptime across all products and data services.

The products are widely used across various industries, including finance, real estate, cryptocurrency, commodities, and government. They provide tailored insights for tasks like tracking voter sentiment, optimizing investment strategies, or monitoring brand perception. We offer products that are tailored for both beginners and advanced data professionals.