No Keyword is an Island: In search of covert associations
This work addresses the challenge of keyword interpretation in corpus-assisted discourse analysis, offering a method to re-contextualize keywords, though it is incremental as it adapts an existing technique from marketing to a new domain.
The paper tackled the problem of interpreting isolated keywords in large text corpora by applying Market Basket Analysis (MBA) to reveal covert associations between keywords, demonstrating its utility in a pilot study on migration discourse in Czech media.
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).