10 resultados para election campaigns

em CentAUR: Central Archive University of Reading - UK


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The potential for spatial dependence in models of voter turnout, although plausible from a theoretical perspective, has not been adequately addressed in the literature. Using recent advances in Bayesian computation, we formulate and estimate the previously unutilized spatial Durbin error model and apply this model to the question of whether spillovers and unobserved spatial dependence in voter turnout matters from an empirical perspective. Formal Bayesian model comparison techniques are employed to compare the normal linear model, the spatially lagged X model (SLX), the spatial Durbin model, and the spatial Durbin error model. The results overwhelmingly support the spatial Durbin error model as the appropriate empirical model.

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This article provides an overview and analysis of the Greek June 2012 elections. Placing the elections within the broader framework of the Greek socio-political and economic context, it discusses the electoral campaign and results, juxtaposing them to the 6 May electoral round. The election results confirmed many of the trends of the previous round, including electoral volatility, the fragmentation of the party system and the rise of anti-establishment forces. The main difference was the entrenchment of the pro- versus anti- bailout division and the prominence of the question of Greece’s continued Eurozone membership.

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Politicians call (or call for) referendums with increasing frequency. But how can they know they will win? Looking at the polls is not enough: opinion during referendum campaigns is often volatile. But this chapter shows that there are nevertheless some recurring patterns that allow us to make reasonable predictions in most cases.

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The General Election for the 56th United Kingdom Parliament was held on 7 May 2015. Tweets related to UK politics, not only those with the specific hashtag ”#GE2015”, have been collected in the period between March 1 and May 31, 2015. The resulting dataset contains over 28 million tweets for a total of 118 GB in uncompressed format or 15 GB in compressed format. This study describes the method that was used to collect the tweets and presents some analysis, including a political sentiment index, and outlines interesting research directions on Big Social Data based on Twitter microblogging.