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A BRIEF SURVEY OF ANGLICISMS AMONG SPANISH DIALECTS
JACOB MCCLELLAND
University of Colorado Boulder
In this survey we design a method for comparing the patterns of English lexical borrowing into dialects
of Spanish. Using data collected from Corpus del Español Actual (Subirats & Ortega, 2012), we
compare the frequency of 28 Anglicisms among dialectal subcorpora. We create a model that is
normalized and standardized among the dialectal data. For each token or class of tokens a Relative
Borrowing Score (RBS) may be derived based on the deviation from the model baseline. Overall rates
of borrowing are thus modeled for each country, as well as semantic patterns of borrowing based on
category. A comparison between the rates of particular Anglicisms and native translation equivalents,
is used to evaluate the semantic changes that accompany lexical borrowing. This RBS model is shown
to concur with borrowing patterns attested in previous literature. It can serve as a broad tool for
identifying areas for more detailed research. It may be adapted to more narrow investigations, such as
the distribution of borrowings among sociolects.
Keywords: Anglicism, lexical borrowing, dialectal variation, semantic modeling, Spanish
1. INTRODUCTION
Lexical borrowing is a significant process in the diachronic evolution of any languages which
exist in prolonged contact. This borrowing is not always a symmetrical process and may be
influenced by unbalanced power dynamics such as colonialism or the prominence of one language
as a lingua franca for communicating broadly among speakers with diverse linguistic backgrounds.
Factors that impact the types and levels of lexical borrowing are prestige, domain specificity, and
pragmatic constraints on cross-cultural or interlinguistic communication. The impacts of these
factors are realized through a complex interplay of the introduction of terms through their
idiosyncratic use by bilingual speakers and adoption and entrenchment of these terms into the
monolingual lexicon (Poplack et al. 1988).
Diachronic analysis of language contact may take on two methodologies, each relying on a
different type of dataset. First, a researcher may examine longitudinal texts to evaluate the
influence of language contact across extended time periods. Second, one may examine latitudinal
evidence of lexical borrowing across language dialects to make inferences based on the semantic
and even grammatical impact that observed borrowing has had within a language.
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Spanish and English coexist within many countries of the world. In 2015, there were 50 million
heritage Spanish speakers reported living in the United States, with 41 million reporting Spanish
to be their primary language spoken within the home. Of these heritage speakers, 57% report to be
fluent English speakers as well (US Census, 2017). Even for speakers non-fluent in English,
exposure to the English lexicon is inevitable due to contact with bilingual and native English
speakers.
Nearly 60% of the residents of Spain report little to no proficiency in English (Zafra, 2019).
Despite ranking 25th in English proficiency out of 35 European countries ( EF.edu, 2019),
Peninsular Spanish shows high rates of borrowing in domains such as technology, tourism, and
trade. The adoption of Anglicisms into Latin American Spanish is by no means monolithic. The
frequency of borrowings varies significantly by country, both in frequency and domain. Cross-
dialectal borrowing, rather than direct contact with English, is a more prevalent source of
Anglicisms for some Spanish dialects (Mateescu, M., 2017). Countries such as Costa Rica and
Panama are in contact with English speakers due to tourism and large numbers of American
expatriates. Panama has a particularly complex relationship with English due to the quasi-
imperialist influence of America related to the Panama Canal (Alvarado De Ricord, 1982). Despite
its long history of resistance to borrowing from English, trends in Argentina now suggest that
Anglicisms are now becoming a marker of prestige in social stratification. (Larsen, 2014). Due to
this complex diversity of influence that English has had in Latin America, it becomes necessary to
study Anglicisms at the minimum of country level resolution.
2. PROJECT GOALS
For this project, we use contemporary corpus data to perform an analysis of Anglicisms as they
occur in the United States, Puerto Rico, Spain, as well as the 18 Latin American countries where
Spanish is the majority language. We perform a quantitative analysis of the frequency of common
Anglicisms within text resources from these countries. We further analyze the frequency of these
lexical borrowings as it relates to particular domains of use, such as food, technology, and clothing.
We continue with a qualitative analysis on phenomena that we observe in the trends of this data.
We then discuss particular word-pairs and what conclusions may be inferred from the variation
observed among national dialects.
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As to the part of our analysis that focuses on language contact, the expectation is that the
frequency of Anglicisms positively correlate to the English proficiency of speakers within a given
country. We expect that the United States, Puerto Rico, and Mexico will have the highest frequency
of Anglicisms, as there is significant social and geographical contact between English and Spanish
speakers in this region. We expect that nations that historically have had strained relationships
with the United States, such as Cuba and Nicaragua, will exhibit a relatively lower frequency of
lexical borrowing.
This analysis will also examine the types of borrowings that are taking place and what effect
they are having as to the semantic space of the different dialects. For terms with close semantic
equivalence (synonyms/translation equivalents), we expect to see patterns that indicate what type
of influence the adoption of the English lexical items is having on the historically Spanish lexicon.
We expect, as attested in previous literature (Cabanillas et. al, 2007) (Morin, 2006), to see a trend
of Spanish pulling Anglicisms from the technical domain, which is dominated by Global English.
Within countries with high levels of bilingualism and cross-cultural interaction, we expect to see
evidence of Anglicisms pushing their Spanish origin equivalents into culturally specific domains.
3. METHODS
We compile a list of 28 common Anglicisms from contemporary blogs (Kreisha, 2020),
YouTube videos (SpanishPod101.com. 2020) and personal experience. These resources are all
from United States sources and primarily reference Anglicisms reported in United States and
Mexican-American Spanish. For 16 of the Anglicisms, we are able to identify semantically
equivalent lexical terms of Spanish origin. For the words bol and light, we select 2 semantic
equivalents to compare a more complex semantic distribution. In total the wordlist contains the
following number of Anglicisms per category with the number of semantically close words of
Spanish origin shown in the parentheses: Clothing 4 (1), Technology 4 (1), Social 8 (3), Food 5
(5), General 7 (8).
Using the Corpus del Español Actual (Subirats & Ortega, 2012) we compare the relative
frequency of each lexical item in the list. This data is taken from the chart feature of the corpus
interface and provides a frequency per million words for each of the 20 countries and the territory
of Puerto Rico. We do an extensive statistical analysis on this data in order to identify trends and
potential anomalies. For each term, we normalize to the average rate of occurrences across all
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dialects. It is not necessarily the case that this mean value represents any norm for borrowing per
se, but it creates a useful scale for talking about dialects with relatively less (negative value) and
more (positive value) frequency of borrowing. Frequency patterns may vary significantly among
lexical items do to the fact that each occupies a uniquely sized semantic space within the language
and culture. To accommodate this feature, we standardize this space for each item by dividing
each value by a standard deviation taken from the frequency variation for this term across dialects.
For the purposes of this paper, we will refer to this value as a Relative Borrowing Score (RBS). In
principle this method is designed to evaluate any patterns of borrowing and other such variation
across multiple dialects.
After identifying terms that warrant a closer look, we perform a qualitative analysis using the
SketchEngine interface (Kilgarriff et al, 2014). The Spanish Web 2018 (esTenTen18) corpus,
available on SketchEngine, is only divided into subcorpora for European Spanish and Spanish of
the Americas. SketchEngine is useful for forming descriptions of the semantic range of terms,
despite the limitations of its low geographical resolution.
4. RESULTS
The data collected suggest substantive variation of English borrowings among Spanish
dialects. The mean frequencies of borrowings among dialects, overall and per category, were used
as a baseline to evaluate the relative frequency of borrowing per semantic domain. An average
semantic domain for each Anglicism and Spanish heritage word pair was created to establish a
baseline to model semantic interaction. The overall composite frequency of these terms was
considered as a baseline by which to evaluate semantic interactions among dialects.
4.1. QUANTITATIVE ANALYSIS
After the raw frequency of Anglicisms are normalized and standardized, each country and
category receive a composite Relative Borrowing Score. This score reflects the number of standard
deviations from the mean for frequency of Anglicisms. The top scored countries are Spain (0.67),
Chile (0.50), and Peru (0.45). The lowest scored countries are Nicaragua (-0.55), El Salvador (-
0.59), and Bolivia (-0.59). The United States (0.05) and Mexico (-0.06) had an average number of
Anglicisms out of the countries studied. Puerto Rico (0.37) came in 6th in RBS, with a much higher
rate of borrowing than the United States, to which it is a territory.
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FIGURE 1. RELATIVE ANGLICISMS PER DIALECT AND CATEGORY
Figure 2 shows the gradient of RBS per country and category, while Figure 3 shows RBS per
category in the top 10 borrowing countries (0.55 avg) compared to the bottom 11 borrowing
countries (-0.32). The high frequency borrowers tended to adopt specialized terms categories such
as clothing (0.52), food (0.49), and technology (0.40). The lowest frequency borrowers disfavored
borrowing clothing (-0.43) and technology (-0.49) terms. This might suggest less cultural diffusion
of global commercial products for these dialects. The lower GDP in these countries may also
correlate with a lower demand for terms to signify technological products. Heavy borrowing in
technology is reflective of a pull pattern of borrowing, as the adopted words fill a semantic void.
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This was evidenced in the fact that we were not able to find translation equivalents for terms in
this category
FIGURE 2. AVERAGE ANGLICISMS PER COUNTRY
FIGURE 3. HIGH/LOW FREQUENCY BORROWINGS PER CATEGORY
The Anglicism frequency scores compared to the Education First English Proficiency Index
(EF.edu, 201) appear to have a moderate positive correlation, but the size of this data sample does
not establish a definitive level of significance (r=0.339, p=.156). There are a few notable
exceptions to this trend: Bolivia and Paraguay have a negative borrowing score, but an above
average proficiency in English. Argentina has the highest proficiency score but has a moderate
frequency of borrowings. It does hold that none of the top countries for Anglicism frequency have
extremely low English Proficiency scores.
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FIGURE 4. RELATIVE BORROWING SCORE & EF ENGLISH PROFICIENCY INDEX SCORES
In an analysis of Anglicisms compared to their Spanish origin semantic equivalents, we add
the normalized frequencies of each token with the normalized frequency of its translation
equivalent, thus estimating their combined share of each semantic domain in the dialect per dialect.
A converse relative frequency would yield a zero score in this analysis. This may suggest that these
terms are semantically equivalent; when the Anglicism is adopted within a dialect, it replaces its
translation equivalent within the semantic space. The bar for mail/correo (Figure 5) reflects this
balanced semantic distribution.
When the combined relative frequency of these semantic pairs has a negative value, the terms
occupy a smaller semantic domain. It is possible these terms belong to a less relevant semantic
domain for that particular dialect. Alternatively, it may indicate that there is some other term not
reflected in this analysis, which compensates within this semantic space. This may indicate that
there are lexical items missing from the analysis, which would increase the vocabulary within this
semantic domain. The heavy left skew of carro/coche in Figure 5 reflects this pattern. While the
analysis suggests that these terms are equivalent in United States Spanish, countries such as
Argentina that use the term auto show a significant negative skew.
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FIGURE 5. SEMANTIC DISTRIBUTION OF WORD PAIRS
When this analysis yields a positive value, the terms occupy a larger semantic domain. This
can be attributed to the terms not being an exact semantic match. The terms are near synonyms,
but they are both used in the dialect therefore increasing the overall frequency. This can be seen
in Figure 5, by the strong right skew to piercing/perfocation. In several countries piercing is
commonly used in the cosmetic sense, while perforcation is used to mean holes punctured in other
contexts. This is an example of push borrowing, in that the native term is somewhat narrowed from
its initial semantic domain.
There are apparent trends within the data which show that our process for choosing semantic
equivalents to be heavily skewed towards particular dialects. Figure 6 demonstrates this with small
and balanced bars for Mexico and the United States, reflecting close matches in the word pairs.
Nicaragua and Bolivia have large bars, indicating that the posited word pairs did not reflect the
patterns of borrowing in these dialects. These are also the two countries with the lowest rate of
Anglicisms.
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FIGURE 6. SEMANTIC SPACE OF WORD PAIRS PER DIALECT
Figure 6 also shows Panama to be an interesting case. As shown by Figures 1 and 2, Panama
has one of the highest rates of English borrowings. Panama also has the broadest semantic space
for the word pairs that we have considered. Perhaps this reflects a phenomenon brought on through
United States imperialism, where multiple registers of prestige inflate the semantic space.
An analysis of two direct translation equivalent tokens is not always the most effective way to
evaluate patterns of borrowing. Terms among languages and dialects will have differently
structured semantic space, as dictated by the culture in which they occur. To look at a more
complex semantic distribution of equivalents within the domain of an particular Anglicism, we
consider bol/cuenco/tazón. Figure 7 shows how the combination of all 3 terms best explains the
interactions within the semantic space. This combination explains the makeup of this semantic
space better than any of the proposed word pairs.
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FIGURE 7. EFFECTIVENESS OF SEMANTIC MODELING WITH THREE TERM SPLIT
While this chart is a good indication of how we may analyze the semantic space it does not tell
the whole story. There are two reasons that a dialect may vary in the frequency of terms for a
particular semantic domain. If it is a cultural norm for food to be eaten by hand, then the semantic
relevance of terms for utensils will be significantly diminished when compared to cultures that
employ utensils. If a culture only has one word to describe utensils, then that word will have a
large semantic domain as compared to a culture that distinguishes among spoons, forks, and
knives. The two highest adopters of bol, Spain and the United States, also have the highest
combined rate for these terms. This suggests either that bowls have a larger semantic relevance in
these cultures or that more items are considered to qualify within a larger semantic domain covered
by these 3 terms, than would be indicated in other dialects. The United States is higher than average
for the use of every one of these three terms. This suggests that these terms are distinctions of
specific types that are relevant in the composition of this larger domain. Latin American countries
with high relative frequency of the term bol tend to have a strong negative correlation between its
use and the combined value of the Spanish origin terms. In Bolivia, the highest Latin American
adopter of bol, the combination of the standardized frequency of these terms equals 0 as compared
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to the mean. In Chile, the second highest adopter, this same value is 0.13. This suggests that this
term may be a direct semantic replacement in these dialects.
4.2. QUALITATIVE ANALYSIS
For our initial analysis, cookie was placed in the category food. It quickly became apparent
that the majority of the instances for the use of this term in fact belonged to the category of
technology. While the singular form had a low rate of borrowing, cookies was the 6th most
prevalent of the words analyzed. This demonstrates how words are not always borrowed from a
language in their dominant sense. Spanish term galleta is the translation equivalent of the English
term cookie in its primary food sense.
FIGURE 8. SPANISH VERB COLLOCATES OF COOKIES (KILGARRIFF ET AL., 2014)
In its technological sense, cookies refers to small files that are downloaded into an internet browser
to track activity. Spanish did not have its own word for these files so it borrowed the English term
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almost exclusively in the plural. Speakers borrowed the term outright and did not reanalyze
galletas in a technological sense. The term cookies has not significantly pushed into the semantic
domain of galletas; it has instead been pulled from English to signify a new technological tool.
FIGURE 9: SPANISH COLLOCATES OF LIGERO AND LIGHT (KILGARRIFF ET AL., 2014)
For the analysis of light we chose ligero and sano as translation equivalents. The attested sense of
this borrowing was to describe diet products or meals that are not heavy. The choice of sano as an
equivalent was not correct, in that Spanish has a distinction sano/saludable that is comparable to
the dwindling distinction in English healthy/healthful. The use of the term light in Spanish is tied
to commercial products from the United States. Coca-cola and Pepsi are 2 of the top nouns in
Spanish that are modified by this adjective. The term has undergone semantic creep in some
dialects and may be used to refer to other healthful or low-fat items. Some dialects, many with a
high frequency of using light, have begun to reanalyze ligero to replace saludable, when referring
to a healthful or a not heavy meal. In other dialects, the reanalyzed ligero may only be used to
mean lightweight.
5. RELEVANCE & FUTURE WORK
The broad nature of the analysis performed in the creation of a Relative Borrowing Score is
effective as a low-resolution signal of patterned borrowing as compared to a baseline. It was
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effective in highlighting borrowing patterns already attested in previous literature (Poplack et al.
1988). Previously attested categories, such as clothing (Balteiro, 2014) and technology (Cabanillas
et. al, 2007) (Morin, 2006), were demonstrated to have high concentrations of borrowing among
countries with high RBS.
This method of analysis may be quite effective for investigating borrowing variation among
sociolects. Ostensibly, speakers from a particular region, due to shared environment and culture,
would share a common semantic field within their lexicon. Social factors can significantly affect
the adoption of borrowed terms (Sánchez, 2017). A shared regional dialect could create a more
stable baseline for an RBS analysis, due to a reduced number of variables. Any variation
demonstrated through this analysis could provide clues as to specific correlates between social
factors and lexical borrowing.
In an analysis of borrowing patterns that reduces free variables, semantic modeling becomes
more practical to describe variation. Observations of how borrowings establish a position within
a semantic field have increased pertinence. Comparing the relative frequency of native and
borrowed terms, as is done in this paper, may be paired with contemporary methods of vector
space analysis (Ganesh et al., 2017).
6. CONCLUSION
The analysis of the frequency of English borrowings into Spanish dialects has yielded many
informative results. It was surprising to find that the United States and Mexico only shows a
moderate rate of borrowing, when compared to the other countries analyzed. It may be necessary
to examine the scope of the United States subcorpus; it may be the case that Spanish material is
catered to new immigrants with less exposure to English. Bilingual speakers may be more likely
to obtain news and other online media from English language sources. Mexico has one of the
lowest scores in the EF English Proficiency Index. This may explain why, despite close
geographical proximity and cultural contact with the United States, the Mexican dialect only has
an average rate of English borrowings.
Cultural contact does seem to be a factor that influences the extent of English borrowings.
Cuba, Bolivia, and Paraguay have moderate to high rates of English proficiency, but due to limited
cultural contact, they have a low rate of Anglicisms within their dialects.
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As we further discuss in the conclusion, other factors may also influence the frequency of
borrowings such as language attitudes. Argentina has a history of laws discouraging language
mixing. Until recently, Argentina even had regulations prohibiting non-Spanish spellings for legal
names (Warren, 2015). Recent adoption of Anglicisms into the Argentine dialect has been tied to
a globalist trend in the higher economic classes. This history of language regulations and attitudes
may explain why the Argentinian dialect has an average frequency of Anglicisms, despite having
the highest English proficiency of Spanish speaking countries.
Technology was not the most heavily borrowed category for countries with a high RBS. Terms
for clothing and food were borrowed more frequently. It is the case that the countries who
borrowed technological terms the least, are also the ones that had the lowest rate of borrowings.
These are also countries with low per capita GDP and low cultural contact with the United States.
A promising addendum to our broader RBS model, is the method employed for analyzing
relative semantic space. Comparing the relative rates of borrowings and native terms appears to be
a fruitful method for modeling semantic change due to language contact. While none of these
models are definitive for identifying semantic shift, skews to the semantic distribution of the bars
in Figures 5 & 6 are suggestive as to whether replacement or semantic narrowing is taking place.
The comparing the Anglicism bol to two terms of Spanish origin, was effective in demonstrating
how complex semantic relationships can vary across dialects.
Finally, we observed how qualitative analysis may be necessary to describe certain patterns of
borrowing. The categorical significance of a borrowing may be lost if an Anglicism is analyzed
based on its primary English sense. Anglicisms may also have effects on Spanish origin terms by
causing a reanalysis of a Spanish origin word to be used in an English sense.
This paper functions as good proof of concept for this type of analysis. There are several tasks
necessary to affirm the significance of these findings. For analyzing the relative rate of borrowings
per country and per category, it will be necessary to develop a much broader list of Anglicisms to
be tested. The word list should take into account the most common Anglicisms as researched for
each dialect, not just Mexico and the United States. It may be further necessary to evaluate each
subcorpus to see if there is a balanced distribution of media type (news, blogs, government
documents).
For the semantic analysis, a more developed list of semantic equivalents is necessary. When a
low skew is modeled for a word pair, additional words should be added for a more complete model.
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For word pairs with a high skew, a qualitative analysis should be done to check for the semantic
specialization that may be indicated.
Each dialect merits an evaluation of the factors that lead to its relative rate of borrowing. The
reasons for variation posited in this paper were made through cursory observations based on the
demographic information available for each country. Economics, global relations, language
attitudes, and relative contact exposure should also be accounted for.
The most compelling application of this method is its ability to model the variation of
borrowing among Spanish dialects. This broad type of analysis accomplished through a Relative
Borrowing Score is effective for identifying borrowing patterns of interest for more detailed
investigation.
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