  While the number and variety of models to explain opinion exchange dynamics
is huge, attempts to justify the model results using empirical data are
relatively rare. As linking to real data is essential for establishing model
credibility, this Letter develops a empirical confirmation experiment by which
an opinion model is related to real election data. The model is based on a
representation of opinions as a vector of $k$ bits. Individuals interact
according to the principle that similarity leads to interaction and interaction
leads to still more similarity. In the comparison to real data we concentrate
on the transient opinion profiles that form during the dynamic process. An
artificial election procedure is introduced which allows to relate transient
opinion configurations to the electoral performance of candidates for which
data is available. The election procedure based on the well--established
principle of proximity voting is repeatedly performed during the transient
period and remarkable statistical agreement with the empirical data is
observed.
