Network Structure Explains the Impact of Attitudes on Voting Decisions

Attitudes can have a profound impact on socially relevant behaviours, such as voting. However, this effect is not uniform across situations or individuals, and it is at present difficult to predict whether attitudes will predict behaviour in any given circumstance. Using a network model, we demonstrate that (a) more strongly connected attitude networks have a stronger impact on behaviour, and (b) within any given attitude network, the most central attitude elements have the strongest impact. We test these hypotheses using data on voting and attitudes toward presidential candidates in the US presidential elections from 1980 to 2012. These analyses confirm that the predictive value of attitude networks depends almost entirely on their level of connectivity, with more central attitude elements having stronger impact. The impact of attitudes on voting behaviour can thus be reliably determined before elections take place by using network analyses.Comment: Final version published in Scientific Report

Corrections on the Thermometer Reading in an Air Stream

A method is described for checking a correction formula, based partly on theoretical considerations, for adiabatic compression and friction in flight tests and determining the value of the constant. It is necessary to apply a threefold correction to each thermometer reading. They are a correction for adiabatic compression, friction and for time lag