This paper aims at modeling the structure of theater reviews based on contemporary London performances by using text zoning. Text zoning consists in tagging sentences so as to reveal text structure. More than 40 000 theater reviews going from 2010 to 2020 were collected to analyze two different types of reception (journalistic vs digital). We present our annotation scheme and the classifiers used to perform the text zoning task, aiming at tagging reviews at the sentence level. We obtain the best results using the random forest algorithm, and show that this approach makes it possible to give a first insight of the similarities and differences between our two subcorpora.