Chronological corpora are collections of texts ordered in time. In bag-of-words approaches, data are typically the frequencies of individual words in the set of texts being grouped into equal-distant time points. In our work the temporal course of a word occurrence is viewed as a proxy of a word life-cycle: recognition of temporal shapes and clustering of words having similar life-cycles are the basic objective. However, the strong asymmetry of frequency spectrum typical of textual data has to be taken into account when defining the specific purpose of clustering and, hence, any type of further processing of data. By adopting a functional data approach and a distance-based curve clustering, the effect of selected data transformations on the generation of word groups is examined.