EU&I 2024 shows the overlap between the political parties’ positions and the user's preferences. In order to simplify the interpretation of the results, the latter are expressed in terms of a percentage of overlap. 0% indicates that a political party and a user’s preferences do not overlap at all, 100% indicates that they completely overlap.
Technically, for calculating a user’s closest candidate, we use the so called “Manhattan (or city-block) distance”, which expresses how close the two respective points are one from another in an n-dimensional space.
At the heart of EU&I 2024 lies a series of political arguments – or issues - on which it is possible to take a position. For example, EU&I 2024 offers to users to take a position regarding the statement "euthanasia should be legalised". Users can choose from the following answer categories: 'I completely agree', 'I tend to agree', 'I’m neutral', 'I tend to disagree' and 'I completely disagree'. EU&I 2024 also allows users to choose the option 'no opinion'.
For calculating the overlap, we first translated the answers given by the users into numbers, using the following key:
 
'I completely disagree' = 0,
'I tend to disagree' = 25,
'I am neutral' = 50,
“I tend to agree' = 75,
'I completely agree' = 100.

The same values were given to the positions taken up by the political parties. We then started off to calculate the distance (k) between the positions (P) of each user (i) and political party (e) on every statement (v). Expressed as an equation, this looks like this:

We also gave the users the possibility to indicate how important individual issue statements were for them. Thus, they could give weights to their answers. When users did so, the distance between a user’s positions and the positions of the political party were multiplied by a weight (W): for issues that were given less weight by a user (through the negative sign -) the distance was multiplied by 0.5. If no particular weight was indicated (in this case the weighting remained neutral, as expressed by the neutral sign =) the multiplication used the factor 1. In case of a statement that was given more weight (expressed by the positive sign +), the calculated distance was multiplied by a factor of 2. Mathematically, the weighted distance therefore becomes:

Every statement can have some effect on one or more radar dimensions. The resultant effect is defined with values: 1 (positive polarity), -1 (negative polarity). Positive polarity means that only positive answers (50-100) increase the value and negative polarity means that only negative answers (0-50) increase the resulting value. Statements with polarity 0 are not included in a radar dimension calculation.
The resulting value regarding all answered questions (Sd) for a political party or user can vary from 0 to 100, where 100 means total agreement.

The political landscape is based on similar assumptions as the uni-dimensions, but goes a step further. Namely, while the uni-dimensions represent the political spectrum in single, separate dimensions, the political landscape further reduces the complexity of politics and offers only two major dimensions: a European integration, pro-EU/anti-EU dimension (vertical axis) and a sociocultural-economic left-right dimension (horizontal axis).

Both of these dimensions range from zero to one hundred. In order to determine the position candidates and users in this two-dimensional space, their respective coordinates on the X and Y axes need to be calculated.

The initial position of a political party on an axis is 50% (neutral). Its position on an axis is calculated over all statements pertaining to that dimension, using the same formula as the uni-dimensions.

The political landscape representation is based on the assumption that, in most political systems, citizens’ and political parties’ opinions on individual issues can be aggregated to a limited number of issue dimensions. In the graphical representation offered to the user, the position of parties (and of the user) on each axis is the average of all positions across issues pertaining to each dimension.

The computation of such averages, on each of the two axes, depends on a priori considerations, both in terms of which dimension an issue belongs to, and which side of the dimension a specific issue position belongs to.

Both the position of the user and the position of candidates are presented to the viewer as points in a two-dimensional space. Please note that this visualisation does not influence the “Party match” result. Also, five statements were included that do not pertain to any of the two dimensions of the political landscape, or any of the six dimensions of the uni-dimensions; therefore, these contribute to calculate the party matching percentage but do not influence the visualisation tools.