Abstract:

The mapping of research data is a special type of multivariate analysis. Like segmentation or cluster-analysis it is a process of data reduction, conceived in order to reveal main structures behind a multitude of data. What distinguishes mapping from other multivariate methods is the fact that its final result does not consist in numbers . Instead of that the structures are expressed by the location of objects (or variables) in space. Mappings take advantage of the fact that we all are accustomed to read maps. The reason why the orientation by a map seems so easy lies in the fact that maps consequently apply the principle of analogy: what is distant in reality is distant on the paper too and vice versa. The principle of analogy is also the key idea behind mapping. In fact we could describe it as a means for transforming digital data into analogy-type information. Detailed numerical information on media audiences is of course necessary for the practical work of media planning. But media mappings may be useful too because they offer quick orientation and help present the media-"landscape" to people who are not familiar with the technical side of media research and media planning.