Multidimensional Scaling of Feeling Thermometers from the 2015 CCES and 2016 ANES Pilot Study

Below, we use a multidimensional scaling method (metric unfolding) to analyze feeling thermometers data from two recent national public opinion surveys: the 2015 Cooperative Congressional Election Study (CCES) and the 2016 American National Election Study (ANES) Pilot Study. Both surveys asked respondents to rate their feelings towards candidates and groups (for example, Donald Trump, Hillary Clinton, and Muslims) on a 100 point scale. We transform the thermometer ratings into distances and produce a spatial map of the results, much as we would to produce a map of cities from on a spreadsheet of driving distances between the cities.

The results are shown below, with the survey respondents marked as “D”, “R”, and “I” based on their party identification. In both plots, the first dimension (the horizontal axis) represents the familiar partisan-ideological divide, separating liberal/Democratic groups and candidates from conservative/Republican groups and candidates. Groups like scientists and college professors are placed in the center-left, while groups like the police are placed center-right.

We suspect that the second dimension is tapping into establishment vs. outsider divisions in both parties: between Hillary Clinton and Bernie Sanders among Democrats, and between Donald Trump and the other candidates (particularly Jeb Bush) among Republicans. Trump is preferred by the larger cluster of Republican voters in the top-right quadrant of both plots, while Bush is preferred by the smaller clusters of Republicans in the bottom-right quadrants. Cruz and Rubio are both somewhere in between.

Within the parties, respondents’ relative preferences between the candidates do not appear to follow a traditional liberal-conservative divide, but are structured along a separate dimension—perhaps involving establishment vs. outsider attitudes and preferences on cross-cutting issues like free trade.

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