No Keyword is an Island: In search of covert associations

TL;DR

This paper proposes combining keyword analysis with Market Basket Analysis to uncover hidden associations in discourse, demonstrated through a study of migration coverage in Czech media.

Contribution

It introduces the novel application of Market Basket Analysis to corpus linguistics for revealing covert associations between keywords.

Findings

MBA effectively identifies dominant ideological strategies in media discourse.

It reveals how keywords are interconnected within larger thematic frameworks.

The method enhances understanding of discourse context beyond isolated keywords.

Abstract

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).