Picture of a ballot box during elections.
Picture of a ballot box during elections. The professors José M. Pavia from the Universitat of València, and Rafael Romero from the Universitat Politécnica de Valencia, have developed a new algorithm to able to decipher individual electoral behaviour from aggregated data. The new procedure has been published in Sociological Methods and Research, a prestigious journal of social science methodology. The new algorithm, implemented in the free software R, will allow media, political parties and election researchers to answer new questions to better inform their audience, to design better election marketing strategies or to find answers to apparent enigmas. Jose M. Pavia is a full professor of Quantitative Methods at the Universitat of València and director of the group in electoral Processes and Public Opinion. Rafael Romero is a full professor (retired) of the Universitat Politécnica de Valencia. Although polls allow the so-called vote transfer matrices to be approximated, they have a number of limitations that make it imposible to use them on many ocassions. On one hand, there are many elections (municipal or historical) where polls are not available. On the other, the results that they offer are very general. The new algorithm allows to answer questions from historical elections, small electoral places and having an estimation of vote transfer matrices from the census tract level. This will allow to study why the behaviour isn't the same in all the neighbourhoods and to know the variables that explain this different behaviours. So questions like: where do the Vox votes come from?
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