In this article, we present the method we used to create a middle-sized corpus using targeted web crawling. Our corpus contains news portal articles along with their metadata, that can be useful for diverse audiences, ranging from digital humanists to NLP users. The method presented in this paper applies rule-based components that allow the curation of the text and the metadata content. The curated data can thereon serve as a reference for various tasks and measurements. We designed our workflow to encourage modification and customisation. Our concept can also be applied to other genres of portals by using the discovered patterns in the architecture of the portals. We found that for a systematic creation or extension of a similar corpus, our method provides superior accuracy and ease of use compared to The Wayback Machine, while requiring minimal manpower and computational resources. Reproducing the corpus is possible if changes are introduced to the text-extraction process. The standard TEI format and Schema.org encoded metadata is used for the output format, but we stress that placing the corpus in a digital repository system is recommended in order to be able to define semantic relations between the segments and to add rich annotation.