📚 Interpreting your results

Like with any other kind of data analysis, in causal mapping you have to be careful to interpret your results correctly.

One thing to think about is, have you coded only explicit causal claims or have you also coded, for example:

• hypothetical links
• dreams / hopes / fears / wishes for the future
• statements that there is NO causal connection between two things, e.g. a quack cure and an illness

Usually we will code this kind of link using dedicated hashtags. You will probably want to exclude links like this from your normal analysis, and treat them separately.

There are quite a few other potential pitfalls! One of them is the transitivity trap, so have a read of that section of the Guide.

You can practice your interpretation skills in this quiz section and the ones after it.

[To be completed]