Abstract
The use of metaphor in cybersecurity discourse has become a topic of interest because of its ability to aid communication about abstract security concepts. In this paper, we borrow from existing metaphor identification algorithms and general theories to create a lightweight metaphor identification algorithm, which uses only one external source of knowledge. The algorithm also introduces a real time corpus builder for extracting collocates; this is, identifying words that appear together more frequently than chance. We implement several variations of the introduced algorithm and empirically evaluate the output using the TroFi dataset, a de facto evaluation dataset in metaphor research. We find first, contrary to our expectation, that adding word sense disambiguation to our metaphor identification algorithm decreases its performance. Second, we find, that our lightweight algorithms perform comparably to their existing, more complex, counterparts. Finally, we present the results of several case studies to observe the utility of the algorithm for future research in linguistic metaphor identification in text related to cybersecurity texts and threats.
Highlights
Metaphor has been a subject of study in cognitive psychology, linguistics, and Natural Language Processing (NLP) for years
If the target word does not exist in the list of concreteness ratings [40], the algorithm cannot decide whether the candidate is metaphorical
Metaphor is a method used to communicate about abstract concepts
Summary
Metaphor has been a subject of study in cognitive psychology, linguistics, and Natural Language Processing (NLP) for years. The widely known Conceptual Metaphor Theory (CMT), laid out by Lakoff and Johnson [1], suggests that “the essence of metaphor is understanding and experiencing one kind of thing in terms of the other“ [1]. People naturally use terms from a concrete or well understood source of knowledge (i.e., “source” domains) and apply them to abstract, or less understood areas of knowledge (i.e., “target” domains) to transfer knowledge [1, 2]. The mapping of knowledge from source to target domains, known as the conceptual metaphor, is complex, linguistic metaphors are common. Research shows that metaphorical language occurs, on average, in one in three sentences [3]
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
