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      Forecasting elections results via the voter model with stubborn nodes

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          Abstract

          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 in any election. We obtain a mean absolute error of 4.74\%. As a side product, our parameters estimates provide meaningful insight on the political landscape, informing us on the quantity of voters that are strongly pro and against the considered parties.

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          Author and article information

          Journal
          22 September 2020
          Article
          2009.10627
          62b3addb-a004-4d7d-8593-8360e1ac05d6

          http://creativecommons.org/licenses/by-nc-sa/4.0/

          History
          Custom metadata
          15 pages
          cs.SI cs.LG

          Social & Information networks,Artificial intelligence
          Social & Information networks, Artificial intelligence

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