An insulin pump? Identifying figurative links in the construction of the drug lexicon (2022)

Abstract: One of the remarkable characteristics of the drug lexicon is its elusive nature. In order to communicate information related to drugs or drug trafficking, the community uses several terms that are mostly unknown to regular people, or even to the authorities. For instance, the terms jolly green, joystick, or jive are used to refer to marijuana. The selection of such terms is not necessarily a random or senseless process, but a communicative strategy in which figurative language plays a relevant role. In this study, we describe an ongoing research to identify drug-related terms by applying machine learning techniques. To this end, a data set regarding drug trafficking in Spanish was built. This data set was used to train a word embedding model to identify terms used by the community to creatively refer to drugs and related matters. The initial findings show an interesting repository of terms created to consciously veil drug-related contents by using figurative language devices, such as metaphor or metonymy. These findings can provide preliminary evidence to be applied by law agencies in order to address actions against crime, drug transactions on the internet, illicit activities, or human trafficking.

## introduction drug trafficking is a sensitive issue, apart from being a social taboo to some people. unfortunately, this is a growing phenomenon that is impacting our lives on different layers. our language is a sample of such impact. nowadays, it is common to hear or read about drugs everywhere, but the words to name them are not necessarily the ones we are used to hear. terms such as cocaine, marijuana, crack, or heroine have been replaced by new items, which at first glance seem to be totally unconnected to the context of drugs. joy, candy, horse, or insulin are new labels used by the community to refer to drug-related contents. some of them turn quite frequent in mass media and, consequently, in our daily communication; therefore, one can find them registered in specialized dictionaries or lexicons. some others, on the other hand, are completely obscure to regular people, or even to the authorities. in this context, the drug trafficking lexicon does not refer exclusively to the jargon to name drugs, but also to the terms used to refer to matters related to them. for instance, production of illegal substances (colitas (joint)), criminal gangs (tacuaches), or even, political speech (sembrar (use/fabricate false evidence)). in this respect, the drug trafficking lexicon is not only used by drug traffickers or by drug addicts. it has reached all social strata and is used by different actors. furthermore, the drug trafficking lexicon underlines how this phenomenon permeates society through language: the fact of constantly being exposed to such lexicon makes this phenomenon something natural to everyone. therefore, the consequences of violence, corruption, or institutional collapse derived from the use and sale of illegal drugs tend to be normalized. given this context, below we describe an ongoing research to identify drug-related terms by applying machine learning techniques. our focus is on making explicit what people consciously (creatively) aim to veil regarding the drug trafficking lexicon. specifically, we are interested in applying nlp techniques to identify figurative devices, such as metaphor or metonymy, as they are understood in cognitive grammar (see @xcite ). to this end, we built a data set about drug trafficking in spanish. this data set contains documents from different sources, such as press, blogs, song lyrics, or political speech. all of them were retrieved from mexican sites; thus, the data set could be regarded as representative of the mexican dialect and setting. the data set was used to train a simple word embedding model to identify links between the known terms and the ones created by means of figurative language. for instance, items such as cocaine, heroine, or drug (known terms) share similar representations with the ones found in woman, or insulin (figurative terms). with this study, we aim to provide preliminary evidence that can be applied by law agencies, for instance, to address actions against crime, drug transactions on the internet, illicit activities, human trafficking, among others. the rest of the article is organized as follows: in section 2 we describe and exemplify the notion of drug trafficking lexicon. likewise, we provide a brief review about the scientific papers about the topic. in section 3 we introduce the data set and detail the experiments that we carried out. in section 4 we report the results and discuss the possible implications. finally, in section 5 we present the final remarks and some pointers to address the future work. ## the drug trafficking lexicon at first glance, the drug trafficking lexicon could be regarded as slang, or even as a non-standard vocabulary. either way, it is common to think that it is only used by some isolated social groups. however, this type of language has gone from marginalization to daily speech in several countries. mexico is a fair example of it. for instance, in the mexican context, it is quite natural to hear in the news about levantones to refer to someone that has been kidnapped, and likely killed, by a criminal gang. in fact, the dictionary of mexican spanish (el colegio de méxico) has registered the term levantón, from the verb levantar (to lift up) as the action of kidnapping someone violently. as noted from the example, the drug trafficking lexicon describes more than drug names. it used to depict a reality in which violence, corruption, and institutional collapse predominate; everything derived from the phenomenon of drug trafficking. with respect to its features, it is necessary to specify that the drug trafficking lexicon is not a language properly; i.e. as far as it has been reported, it has no linguistic particularities to be considered an independent system. it is featured, on the contrary, by a set of lexical items (some of them neologisms) and phrases, whose meaning is often completely obscure to most people. in this regard, the drug trafficking lexicon has compiled an interesting linguistic inventory, which has been fed from different sources, such as mass and social media, literature, political speech, and popular folklore. in this respect, in the field of linguistics, some researchers have addressed their approaches from lexicographical perspectives. in particular, some of them have focused on the latin american context. for instance, @xcite conducted a study about the criminal slang and drugs in colombian prisons. they showed how such criminal jargon is characterized by a frequent use of linguistic devices, such as metaphors and metonymies (this seems to be repeated in the language of drug trafficking in mexico, since the technical lexicon associated with crime is impregnated with metaphorical expressions (see @xcite ). more recently, in a research about the phenomenon of drug trafficking in the north american context, @xcite described that one of the semantic fields in which this type of lexicon changes constantly is that of drug names. he stressed that this fact is evident in the creation of new terms, as well as in the reassignment of new meanings to the existing ones, both in english and spanish. likewise, pressacco (2022) described violence and drug trafficking in mexico from the so called narco language. the author distinguishes two classes to categorize this language: literal and figurative. finally, she provides an interesting list of terms, phrases and constructions to exemplify the drug dealers argot. in different locations and specialized areas, sanmartín (1998) analyzed the jargon of the criminals in spain. she described some linguistic mechanisms to characterize this lexicon, in particular, synonymy and polysemy. on the other hand, torregrosa and sánchez- @xcite , in their study about english law enforcement, analyzed the use of conceptual metaphors related to drugs for educational purposes in the training of lawyers. finally, in a computational approach, @xcite worked with narco language from a nlp perspective. they suggested a representation of narco-related concepts by identifying triggers of criminal content in corpus. ## unveiling figurative language in this section, we firstly describe the data set used to build the word embedding model; then, we detail the processes to identify the figurative terms. ## results the result of the previous processes is a set of 505 drug-related terms; i.e. an average of 3 unrelated items per known term. subsequently, we analyzed the vectors of the 505 candidates in order to recognize elements to connect them to the drug trafficking context. this is clearer if we observe figure 2 : from the 10 most similar words for aguacate, the items churros (marijuana), mulas (drug trafficker), tachas (cocaine), and fuman (inflectional form of the verb to smoke) are totally drug-related. the same fact for chiva. the words inyecto, meto (inflectional forms of the verbs to inject and to do drugs, respectively), and chochos are commonly used by the community to refer to drugs. this fact corroborates that some of the unconnected items are closely linked to the context of drugs. however, there were others items whose vectors proved the contrary. for instance, tomate, from fig. 1 , whose 10 most similar words referred to food only. given this result, it could be stated that some unconnected items are, in fact, figurative terms to implicitly express drug-related content. nonetheless, such assumption should be assessed by the experts; i. e. we could identify some unrelated terms regarding drug trafficking; however, we are not capable of saying that they mean anything to the community. in addition, there is not labeled data to compare our findings. therefore, in order to provide arguments to validate our findings, we contacted an expert on the topic in mexico. this expert has published several academic papers and some books about narco and, specifically, about narco language. prior to contacting the expert, we grouped the unrelated terms in clusters with the purpose of identifying an underlying semantic structure. to this end, we ran a similarity analysis for the 505 terms considering their co-occurrences in the whole data set. figure 3 shows a sample of the clusters presented to the expert. ## conclusions and future work in this study we have approached an unusual phenomenon in natural language processing: the drug trafficking lexicon. our focus was on automatically identifying possible figurative terms to refer to drug-related contents in spanish. to this end, we used a data set about drug trafficking in mexico and built a word embedding model to identify the terms. the results showed that the model could identify a set of supposed unrelated terms to the domain. those terms were validated by a human expert; however, only 30% of them are cryptic terms. this means, although they are known by the community, people out of the drug trafficking context do not know them. therefore, they can be used to veil criminal content. finally, we have outlined a possible explanation about their successful usage within the domain. in this respect, although this is still work in progress, we have suggested that this can be explained in terms of figurative devices, such as metaphor and metonymy, which according to the cognitive linguistics foundations @xcite , are part of our conceptual structure. as future work, it is planned to collect data from other variants to extend the scope of this approach, as well as to deepen the analysis of the linguistic mechanisms to better understand how this lexicon works to successfully communicate veiled information within a complex linguistic system. thus, the insights could shed light on how this social phenomenon has linguistically permeated our society in broader terms. to conclude, we consider that works like this one could provide evidence to be applied to address actions against different illicit activities.