Beyond big data – new techniques for forecasting elections using stochastic models with self-organisation and memory
- DOI
- 10.1016/j.techfore.2021.121425
- Published
- 2022-02-01
- Container
- Technological Forecasting and Social Change
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.1016/j.techfore.2021.121425,
title = {Beyond big data – new techniques for forecasting elections using stochastic models with self-organisation and memory},
author = {Dmitry Zhukov and Tatiana Khvatova and Carla Millar and Elena Andrianova},
year = {2022},
journal = {Technological Forecasting and Social Change},
doi = {10.1016/j.techfore.2021.121425},
url = {https://doi.org/10.1016/j.techfore.2021.121425}
}RIS
TY - JOUR TI - Beyond big data – new techniques for forecasting elections using stochastic models with self-organisation and memory AU - Dmitry Zhukov AU - Tatiana Khvatova AU - Carla Millar AU - Elena Andrianova PY - 2022 JO - Technological Forecasting and Social Change DO - 10.1016/j.techfore.2021.121425 UR - https://doi.org/10.1016/j.techfore.2021.121425 ER -
APA
Zhukov, D., Khvatova, T., Millar, C., & Andrianova, E. (2022). Beyond big data – new techniques for forecasting elections using stochastic models with self-organisation and memory. Technological Forecasting and Social Change. https://doi.org/10.1016/j.techfore.2021.121425
Source records
- hal · retrieved 2026-09-26T14:05:52.509Z