Sociological Cycles: The Accumulated Discrepancy Between Appearance and Reality as Driver
First published: 2023
Brief summary
Proposes an oscillator-circuit-inspired mathematical model for sociological cycles, illustrated with a ~10-year oscillation found in the historical popularity (citation frequency) of painter Marc Chagall in the UK and Germany.
Article
Sociological Cycles: The Accumulated Discrepancy Between Appearance and Reality as Driver is a preprint published by arXiv in 2023. It focuses on proposes an oscillator-circuit-inspired mathematical model for sociological cycles, illustrated with a ~10-year oscillation found in the historical popularity (citation frequency) of painter Marc Chagall in the UK and Germany.
The analysis focuses on slightly less than 10 years (fashion/popularity cycle). The data source is Google Books culturomics citation-frequency data for Marc Chagall, 20th century. This gives the cycle claim a specific numerical and evidential setting rather than presenting periodicity only as a visual impression.
The article reports the following result: Apart from a slight overall increase, curves of Chagall citation frequency in the UK and Germany both show oscillations with a period slightly less than 10 years, understood as a typical fashion cycle. The interpretation is strongest when it survives detrending, autocorrelation controls, structural-break tests and comparison with stochastic or random-walk alternatives.
For cycles researchers, the article brings together sociological cycles, fashion cycles, chagall popularity, oscillator model. It is relevant to social-cycle research because apparent waves in historical or behavioural data must be separated from seasonality, autocorrelation, structural change and random walks.
Because it is a preprint, the work should be read alongside later peer-reviewed publications and independent replications. It remains useful because the proposed cycle, dataset and analytical approach are stated clearly enough to be scrutinised.
Source details and credits
- Source / publisher: arXiv
- Source type: Preprint
- URL type: PDF
- Credits: arXiv
- URL: https://arxiv.org/pdf/2309.14772