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Data from the GIPEyOP online election poll for the 2015 Spanish General election.
Pavía, José M; Coll-Serrano, Vicente; Cuñat-Giménez, Rubén; Carrasco-Arroyo, Salvador.
Afiliación
  • Pavía JM; GIPEyOP, UMMICS, Department of Applied Economics, University of Valencia, Spain.
  • Coll-Serrano V; Department of Applied Economics, University of Valencia, Spain.
  • Cuñat-Giménez R; Department of Applied Economics, University of Valencia, Spain.
  • Carrasco-Arroyo S; Department of Applied Economics, University of Valencia, Spain.
Data Brief ; 31: 105719, 2020 Aug.
Article en En | MEDLINE | ID: mdl-32490084
ABSTRACT
The general elections of 2015 in Spain took place in the middle of the Great Recession after several years of austerity economic policies. This election caused a political earthquake that shook the Spanish party system. During the campaign of that election, GIPEyOP (Elections and Public Opinion Research Group from University of Valencia) conducted a survey to collect relevant data about the electorate beliefs, intentions and motivations. This article describes the data set attained, which comprises 71 variables after removing, to ensure full anonymity, those variables that would potentially allow respondents to be identified. Respondents answered a self-administered online questionnaire and were recruited using chain sampling. A total of 14,261 valid observations were collected between 27th November and 18th December 2015. GIPEyOP employed the data collected up to 14th December to deliver a prediction of the election outcomes during that election campaign. Among other issues, this data set may be reused to assess theories of expectations' formation, to spot how social networks spread geographically and to measure gender, age and education technological gap of the Spanish population.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Data Brief Año: 2020 Tipo del documento: Article País de afiliación: España

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Data Brief Año: 2020 Tipo del documento: Article País de afiliación: España