  This paper describes how corpus-assisted discourse analysis based on keyword
(KW) identification and interpretation can benefit from employing Market basket
analysis (MBA) after KW extraction. MBA is a data mining technique used
originally in marketing that can reveal consistent associations between items
in a shopping cart, but also between keywords in a corpus of many texts. By
identifying recurring associations between KWs we can compensate for the lack
of wider context which is a major issue impeding the interpretation of isolated
KWs (esp. when analyzing large data). To showcase the advantages of MBA in
"re-contextualizing" keywords within the discourse, a pilot study on the topic
of migration was conducted contrasting anti-system and center-right Czech
internet media. was conducted. The results show that MBA is useful in
identifying the dominant strategy of anti-system news portals: to weave in a
confounding ideological undercurrent and connect the concept of migrants to a
multitude of other topics (i.e., flooding the discourse).
