Beyond big data – new techniques for forecasting elections using stochastic models with self-organisation and memory
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DOI: 10.1016/j.techfore.2021.121425
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- Zhukov, Dmitry & Khvatova, Tatiana & Lesko, Sergey & Zaltcman, Anastasia, 2018. "Managing social networks: Applying the percolation theory methodology to understand individuals' attitudes and moods," Technological Forecasting and Social Change, Elsevier, vol. 129(C), pages 297-307.
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- Wu, Zhonghuan & Duan, Chunlin & Cui, Yuting & Qin, Rong, 2023. "Consumers' attitudes toward low-carbon consumption based on a computational model: Evidence from China," Technological Forecasting and Social Change, Elsevier, vol. 186(PA).
- Zhao, Jianyu & Yu, Lean & Xi, Xi & Li, Shengliang, 2023. "Knowledge percolation threshold and optimization strategies of the combinatorial network for complex innovation in the digital economy," Omega, Elsevier, vol. 120(C).
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Keywords
Social process modelling; Stochastic dynamics; Self-organization; Memory; Probability density oscillations; Electoral processes;All these keywords.
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