Forecasting elections results via the voter model with stubborn nodes

@article{Vendeville2021ForecastingER,
  title={Forecasting elections results via the voter model with stubborn nodes},
  author={Antoine Vendeville and Benjamin Guedj and Shi Zhou},
  journal={Applied Network Science},
  year={2021},
  volume={6},
  pages={1-13}
}
In this paper we propose a novel method to forecast the result of elections using only official results of previous ones. It is based on the voter model with stubborn nodes and uses theoretical results developed in a previous work of ours. We look at popular vote shares for the Conservative and Labour parties in the UK and the Republican and Democrat parties in the US. We are able to perform time-evolving estimates of the model parameters and use these to forecast the vote shares for each party… 

Figures and Tables from this paper

References

SHOWING 1-10 OF 43 REFERENCES
UK Election Statistics: 19182019 – A Century of Elections, 2020
  • URL https://commonslibrary.parliament. uk/research-briefings/cbp-7529/
  • 2020
A Meta-Analysis of State-of-the-Art Electoral Prediction From Twitter Data
TLDR
It is revealed that its presumed predictive power regarding electoral prediction has been somewhat exaggerated and further work on this topic is required, along with tighter integration with traditional electoral forecasting research.
No, You Cannot Predict Elections with Twitter
TLDR
While simple approaches are purported to be good enough, the predictive power of Twitter regarding elections has been greatly exaggerated, and difficult research problems still lie ahead.
Sentiment Aggregate Functions for Political Opinion Polling using Microblog Streams
TLDR
A large set of sentiment aggregate functions are investigated and a regression analysis using political opinion polls as gold standard is performed, showing that different sentiment aggregate function exhibit different feature importance over time while the error keeps almost unchanged.
Multi-cycle forecasting of congressional elections with social media
TLDR
A new estimator is introduced that models the language of campaign-relevant Twitter messages and out-performs incumbency in out-of-sample tests for the 2010 election on which it was trained, but collapses when the same algorithm is used to forecast the 2012 election.
Towards Passive Political Opinion Polling using Twitter
TLDR
The automated senti- ment analysis of tweets from UK Members of Parliament (MPs) towards the main political parties is investigated and the volume and sentiment of the tweets from other users are investigated as a proxy for their voting intention and the results are compared against existing poll data.
Towards Control of Opinion Diversity by Introducing Zealots into a Polarised Social Group
TLDR
This work explores a method to influence or even control the diversity of opinions and introduces zealots into a polarised social group to do so.
BREXIT Election: Forecasting a Conservative Party Victory through the Pound using ARIMA and Facebook's Prophet
TLDR
The results found that the ARIMA and Prophet models were effective and proficient in forecasting the polls prediction on the 4th December, 2019 of a Conservative win by validation of forecasted increases in the pound.
Data for the United Kingdoms elections is available online
  • Data for the United States elections has been crawled from Wikipedia
  • 2020
Inferring the votes in a new political landscape: the case of the 2019 Spanish Presidential elections
TLDR
This article aims to predict the results of the 2019 Spanish Presidential election and the voting share of each candidate, using Tweeter and develops a political lexicon-based framework to measure the sentiments of online users.
...
1
2
3
4
5
...