Source Domain Associations as Conceptual Assemblages in Trauma Talk – an Association Rule Mining Approach

ABSTRACT

The qualitative nature of co-deployed or “associated” metaphorical source domains in discourse has been extensively researched, often in terms of whether they share common conceptual roots. There are however few empirical studies on the strength of these associations and their implications. In mental healthcare activities like psychological interviews and counseling, for example, strongly associated sources may suggest unique “conceptual assemblages” that highlight underexplored (dis)similarities between clients or client groups, beyond the typical focus on isolated sources and frequencies. Our case study compares source domain associations produced by two interviewee groups – one meeting the diagnostic threshold for acute stress disorder (ASD), the other not – relating their first-hand experiences of traumatic events during the 2019 Hong Kong social unrest. The machine learning method of association rule mining is used to extract and quantify the top association rules in both groups. Results show i) a shared rule suggesting a highly schematic construal of trauma that nevertheless varies in instantiating details, and ii) several distinct rules that corroborates and lends further insight into the “agentive vs. non-agentive” characteristics exhibited by ASD vs. non-ASD individuals. Implications and future directions, including potential extensions to other discourse contexts, are discussed.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

¹ Both acute stress disorder (ASD) and posttraumatic stress disorder (PTSD) are common conditions after witnessing or experiencing a traumatic event. While they share symptoms like anxiety, nightmares, avoidance and reexperiencing of trauma, a key difference is that in ASD symptoms typically develop within a month after the event, do not persist for more than a month, and are less severe, while in PTSD symptoms may not appear until much later, are more severe, and can last for years. ASD is investigated in this study as data collection would be more practical and manageable.

² Because of the enormous number of itemsets that can be generated from just a few items, we need to predetermine the maximum number of items per set, as well as the minimum number of transactions they must appear in, to be considered. The decisions taken for this study are further explain in the data and methods section.

Additional information

Funding

This work was supported by the Hong Kong Polytechnic University [1-ZVY8].