![]() Nevertheless, studying just absolute (variance) or relative (Fano factor) fluctuations can give misleading conclusions when the system’s size is ignored. There are multiple ways to quantify fluctuation levels, including the variance (or standard deviation), Fano factor 8, and coefficient of variation 9. In financial engineering,įorecasting the volatility of stock prices 5, 6 is central to hedging strategies for stock portfolios 7. When thermal activity 1 or heart rate variability are measured 2, they can give meaningful information if system-specific features are taken into account, such as the fluctuation–dissipation theorem 3, or norms for heart rate variability in various groups of people 2, 4. The results suggest that news outlets with a liberal bias tended to be the least reactive while conservative news outlets were the most reactive.įluctuations occur everywhere and are frequently sources of useful knowledge about intrinsic properties of systems, with diverse applications. Combining our method with the political bias detector Media Bias/Fact Check we quantify the relative reporting styles for different topics of mainly US media sources grouped by political orientation. Our approach distinguishes between different news outlet reporting styles: high reactivity points to activity fluctuations larger than expected, reflecting a bursty reporting style, whereas low reactivity suggests a relatively stable reporting style. We apply our method to activity records from the media industry using data from the Event Registry news aggregator-over 32M articles on selected topics published by over 8000 news outlets. The first component score is a calibrated measure of fluctuations-the reactivity RA of a given entity. ![]() Differences from the benchmark (residuals) are aggregated across multiple timescales using Principal Component Analysis to reduce data dimensionality. Here we introduce a method that uses predictions from a fluctuation scaling law as a benchmark for the observed standard deviations. However, conclusions based on fluctuations from a single entity can be misleading when used without proper reference to other comparable entities or when examined only on one timescale. A common way to learn about a system’s properties is to analyze temporal fluctuations in associated variables. ![]()
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