Introduction
Audiovisual translation (AVT) or multimedia translation plays an essential role in our lives due to the enormous volume of audiovisual materials that can be accessed through various media and entertainment platforms. AVT has aroused the interest of researchers because it represents a fertile environment for those interested in examining how the linguistic and non-linguistic components of the AV product are transmitted to the audience. Au (2009) defined AVT as a discipline that encompasses a transfer of verbal and non-verbal aspects of audiovisual products, making it a multi-semiotic translation. Subtitling can be considered the most extensively researched mode of AV modes. The two most popular forms in AVT are dubbing and subtitling. Chaume (2020, p. 1) defined dubbing as a type of AVT that “consists of replacing the original track of a film’s (or any audiovisual text) source language dialogs with another track on which translated dialogs have been recorded in the target language.” According to Karamitroglou (2000, p. 5), subtitling is “the translation of the spoken (or written) source text of an audiovisual product into a written target text which is added onto the images of the original product, usually at the bottom of the screen.” Díaz-Cintas and Remael (2014) classified subtitles into three linguistic dimensions: intralingual, interlingual, and bilingual. This study scrutinizss a paralel interlingual corpus of forty English movies along with their Arabic subtitles.
This study combines corpus linguistics and translation studies in what is known as corpus-assisted translation studies. With the advent of personal computers, the initial motive for using corpus linguistics in translation was in the 1990s (Baker, 1993). Corpus-based translation studies involve “the use of corpus linguistic technologies to inform and elucidate the translation process” (Kruger et al., 2011). The translation process is investigated through specialized software explicitly designed to search for particular keywords. The software, in turn, gives statistics and comparisons that help obtain analytical results for the original text and its translations. Examples of software packages include WordSmith (Scott, 2012), AntConc (Anthony, 2013), and SketchEngine (Kilgarriff et al., 2014).
This study adopts a corpus-assisted approach to explore the most frequent translation strategies that professional subtitlers opted for when rendering English swear words into Arabic. It examines the subtitling of English movies into Arabic by investigating the subtitles of swear words in forty movies in four different genres, namely drama, action, sci-fi, and biography. Swear words express the speaker’s sentiments and reactions in an impolite manner (Moore, 2012). Various genres, such as drama, action, and comedy, to mention a few, include different swear words that are used to convey different messages. The translation of swear words is a subject of contention among translators and researchers, especially when dealing with different languages and cultures.
Given that rendering swear words is a demanding task requiring a set of translation strategies, subtitlers need to know how to render the message to the target culture appropriately. This study attempts to answer the following two research questions:
What are the most commonly adopted translation strategies by Netflix subtitlers in rendering English swear words into Arabic?
How were the translation strategies distributed in the four investigated genres, namely drama, action, sci-fi, and biography?
Literature review
Gottlieb (2001, p. 87) defined subtitling as “the rendering in a different language of verbal messages in filmic media in the shape of one or more lines of written text presented on the screen in sync with the original message.” Subtitling could be done by professional translators (subtitlers) and non-professional translators (fansubbers). Díaz-Cintas and Muñoz Sánchez (2006) defined fansubs as a form of subtitles executed by non-professional translators. According to O’Hagan (2007, p. 162), professional subtitling is the “only commercially viable way to efficiently produce subtitles in a wide range of languages with limited time and budget.” Fansubbers are aware that they are translating for an audience with a greater interest in the film’s original culture than the casual viewer (Díaz-Cintas and Muñoz Sánchez, 2006). Consequently, fansubbers often prioritize strategies that provide viewers with an “authentic” experience (O’Hagan, 2007).
This study investigates the translation strategies used to render swear words. The researchers hypothesize that omission will be the most used strategy by Netflix subtitlers. This could be due to some issues related to culture and censorship.
Swearing
There is a lack of agreement when attempting to circumscribe what constitutes swear words from a linguistic perspective (O’Driscoll, 2020). Nodoushan (2016, p. 241) argued that “swear word/cursing, poor language, and filthy language” can be used interchangeably. Likewise, Vingerhoets et al. (2013) pointed out that swearing and cursing are synonyms. Furthermore, in Stapleton (2010) definition, expletives and swear words are synonymous, which is consistent with Ljung (2011) observation that expletives are the prototype of the use of swear words by most people.
The definitions of swearing vary depending on its linguistic, social, and psychological functions. For example, Dewaele (2004) argued that swear and taboo words are multifunctional and pragmatic units that take diverse discourse functions and are identified by their offensiveness. Linguistically speaking, Ljung (2011) defined swearing as the use of utterances comprising prohibited words, typically subject to severe lexical, phrasal, and syntactic constraints, implying formulaic language and having a primarily emotional purpose. Furthermore, some conceptual and functional overlap exists between swearing and other forms of taboo language, such as slurs and discriminatory language (Allan, 2015; O’Driscoll, 2020). Therefore, the efforts at defining, delimiting, and typologizing swear words are united by the fact that they index the perspective of their function.
O’Driscoll (2020) emphasized one critical distinguishing element of swear words, which is related to the potential for such words to be offensive and elicit negative emotions. Swearing is, therefore, by nature, a taboo action. As a result, it is often socially sanctioned or penalized through various informal and formal mechanisms (Stapleton et al., 2022). In addition, Stapleton (2010) hypothesized that swearing serves specific objectives that are difficult to perform through other types of language use. Therefore, swearing creates various unique psychological, physiological, and emotional effects and has interactional and rhetorical outcomes (Stapleton et al., 2022).
Swearing is regarded as inappropriate use of language. Andersson and Trudgill (1992) identified three motives for swearing: linguistic, social, and psychological. Swearing is a linguistic activity that involves the use of taboo words (Stapleton, 2010). Therefore, it is a topic that lends itself to investigation from various linguistic perspectives, including psycholinguistics (Pinker, 2007), pragmatics (Jay and Janschewitz, 2008), sociolinguistics (Hagen, 2013), and semantics (Goddard, 2015). Andersson and Trudgill (1992) defined swearing as language use in which the expression relates to something stigmatized in the swearer’s culture is not intended to be rendered literally, and can be used to convey some emotions or meanings. Swearing is often associated with references to sexuality, genitalia, and religion (Pinker, 2007; Stapleton, 2010).
According to Montagu (2001, p. 71), swearing is “a learned form of human behavior in cultures and under conditions in which it is encouraged.” Social interaction may offer more fundamental insights into the emergence of swearing than solely attributing it to linguistic causes (Song et al., 2022). Research interest is now being paid to the study of swearing from a psychological perspective since it reveals answers to fundamental questions such as, “Why do we swear?” Is there a connection between exposure to positive and negative attitudes and the use of swearing? The investigation of swearing from psychological, social, and linguistic perspectives becomes considerably more approachable once these questions are answered. According to Jay (2009), swearing is not an indication of low intellect and inarticulacy, as is often assumed, but rather an emotional language. Thereby, the correlation between swearing and emotion strengthens the psychological impact of cursing.
Multi-functionality of Swear words (Denotative vs. Connotative Meaning)
Semantics is the study of language meaning. It has two kinds of meaning, namely denotative and connotative. As stated by Crane et al. (1981), denotative meaning is the aspect of a word or phrase meaning that is akin to a definition. Likewise, Omar (2012) argued that a word’s or lexeme’s denotation is its essential meaning as defined in a dictionary. While the connotative meaning is related to psychology and culture and refers to the personal or emotional associations aroused by words. In addition to its literal meaning, a word’s connotation may convey nuanced emotions and judgments. Generally speaking, one may infer that the denotative meaning is the same as the literal dictionary meaning, but the connotative meaning is a culturally dependent meaning (non-literal).
In the context of swear words, there is a debate in the literature about whether or not swear words can be used denotatively or literally (Andersson and Trudgill, 1992; Dynel, 2012; Ljung, 2011; Pinker, 2007). For example, Singleton (2009) offered a triple set of required criteria for swear words: they link to taboo domains, can produce catharsis, and have literal and non-literal meanings. Furthermore, O’Driscoll (2020) argued that the issue is further provoked by the fact that many of the seemingly most offensive English taboo words are employed metaphorically than literally, so that taboo reference is not a factor but rather a form of taboo. Therefore, swear words, by their very definition and use, are judged to be offensive, regardless of whether the meaning in a given context is literal or non-literal, denotative or connotative (O’Driscoll, 2020).
English and Arabic cultures
Language is intertwined with culture as it constitutes an authentic means of communication ingrained in the core of reality, being the “socially acquired knowledge” (Yule, 2020, p. 267). Debbas and Haider (2020, p. 3) argued that “cultural diversity is the source of translation, and translation is the outcome of cultural interchange.” Translation is a communication tool that employs language and culture in the service of each other. Ivarsson and Crofts (1992) pointed out that it is vital to consider the language variety and cultural awareness of the intended audience while subtitling. Researchers have argued that swear words have a significant function in language. In fact, they are often used when people need to vent their feelings and opinions, such as anger, surprise, or dissatisfaction (Jay, 1992). Swearing allows individuals to express their feelings through language, being a linguistic phenomenon worthy of in-depth investigation and analysis (see Chen, 2004; Fernández, 2009).
Swear words are components of every language and culture’s lexicon. Swear words are among the lexical items that are subject to social restrictions (Malenova, 2015). Manchón (2013) claimed that swear words might affect the flow of a movie. Furthermore, some researchers pointed out that the cultural and moral patterns of the target language may not allow translating swear words which are likely to alter throughout the translation process (see Ameri and Ghazizadeh, 2014; Sedighi and Najian, 2012). Therefore, translating swear words from one language/culture into another may be problematic for subtitlers and put them under the criticism of viewers, especially in conservative societies (Haider et al., 2023).
Some audiovisual works produced in English are rife with swear words that may upset some target audiences, especially in conservative societies like the Arab ones. Alabbasi (2009) stated that subtitling requires the adoption of what House (1977) termed a cultural filter. A Cultural filter is a way to capture the social-cultural variations in behavioral norms and stylistic conventions between the source culture and the target culture, viewing the source text through the glasses of the target text members (House, 1977). Consequently, it attempts to naturalize the source text to suit the features of the target cultures and texts. Furthermore, Alabbasi (2009) claimed that American movies, in particular, are riddled with swear words in various situations, which Arab viewers may find repulsive and immoral, especially when such movies are viewed by the whole Arab family with different age groups. Therefore, Alabbasi (2009, p. 186) recommended that “swear words should be filtered and translated with words in the target language of the viewing audience which convey the meaning of swear words (anger, hostility, justification, frustration, insult, scorning, or humiliation), not necessarily in the same degree of vulgarity or offensiveness.”
Swearing is a taboo in languages subject to populist cultures governed by religions, traditions, and morals. Al-Yasin and Rabab’ah (2019) claimed that the Arab culture is well-known for its conservatism and influence of religion on society. Therefore, it is uncommon to hear a plain-spoken taboo word in the Arab media. According to Aqel (2016), four factors may be considered when rendering English taboo words into Arabic media. These factors include culture, religion/beliefs, ideological perspectives, and the channel’s policy. This shows that the religious, cultural, and ideological aspects of the Arab society have the upper hand when deciding which scenes and linguistic expressions to appear and which ones to be weeded out. In this regard, Al-Adwan and Yahiaoui (2018, p. 87) argue that the English and Arabic Languages “are culturally and linguistically distant, and what might be accepted in the West might not be tolerated in the Arab World”.
Modern standard Arabic (MSA) vs. Arabic vernaculars
The Arabic language has different varieties, such as Jordanian, Algerian, and Egyptian, in addition to Modern Standard Arabic (MSA), to mention a few. MSA is the variety used in the subtitling of audiovisual products (Al-Abbas and Haider, 2021). Arabs speak different vernaculars that define their identities within specific geographical areas. At the same time, Modern Standard Arabic (MSA) unites them, serving as a universally recognized communication medium among Arabs. Politeness is one of the major distinguishing characteristics of MSA when compared to spoken vernaculars. Vernaculars are often spoken but not written, which is why they are sometimes associated with impoliteness (Rabab’ah and Alali, 2020). Vernacular Arabic also lacks the prestige of MSA and is often reserved for lowly functions (Suleiman, 1985). Therefore, it is not surprising that spoken Arabic vernaculars have been demoted to serve as a medium for less prestigious functions, taboos, vulgarisms, and swearing. On the other hand, MSA is a respected and cherished form that is seen as a mode of communication for polite and well-educated individuals. This does not imply that MSA never uses impolite language; nonetheless, the language used is often more polished and less offensive (Haider and Hussein, 2022).
Farghal (1995) noted that euphemism as a pragmatic resource in natural language is associated with MSA rather than different Arabic vernaculars since it is profoundly anchored in linguistic politeness reflected in careful speech. Dysphemism, on the other hand, is more prevalent in Arabic vernaculars than in MSA (Farghal, 1995). In the same vein, Haider and Hussein (2022, p. 3) claimed that “words tend to be formal and polite in MSA, while their equivalents in colloquial lack this attribute.”
Consequently, in the case of subtitling swear words using MSA, the target text would definitely be euphemized, mitigated, and polished. Accordingly, it would be difficult to maintain the same level of offensiveness that the swear words have in the source text.
Swear words translation strategies
There are many strategies for rendering swear words and taboo expressions. Several researchers have conducted studies on translating taboo expressions into Arabic (see Al-Yasin and Rabab’ah, 2019; Alsharhan, 2020; Krishan, 2012). Al-Yasin and Rabab’ah (2019) examined the connotative equivalence of taboo words in three American hip-hop movies and their Arabic subtitles. The findings indicated that the Arab fan subtitler successfully rendered taboo words into Arabic through euphemism and omission. These strategies are mainly employed to accommodate cultural constraints. The Arabic subtitles conformed to the connotative functions of English taboo words only when the translator utilized the euphemism technique. In contrast, the connotative functions failed to appear in the subtitles when the translator resorted to omission.
Almijrab (2020) proposed two main strategies for rendering taboos into Arabic, namely substitution and taboo for taboo. The researcher also highlighted that the translator might omit the taboo word from the target text. However, the researcher also argued omission is not the right choice when the ST taboo is crucial; therefore, the translator must adopt euphemism or substitution. In the same vein, Alsharhan (2020) examined the Arabic subtitles generated by Netflix, focusing on taboo language instances. The findings indicated that two significant modifications to the existing subtitling strategies were required, namely euphemism and shift in the register. In addition, the results suggested that a range of subtitling strategies were utilized in rendering taboo words into Arabic on Netflix shows, contrary to prior norms, which often relied on omission and other forms of euphemism. Another significant finding was that approximately half of all taboo language instances are euphemized despite the policy’s non-censorship. Another study conducted by Debbas and Haider (2020) explored the cultural constraints inherent in the Arabic subtitling of the American animated sitcom “Family Guy.” The researchers divided the cultural constraints encountered during translation into three categories: religious remarks, jokes, and humor incorporating proper nouns and taboos. The findings indicated that religious remarks were rendered using scene deletion, word omission, and word omission with justifications. Additionally, the results showed that two strategies were used to translate taboos, namely euphemism, and omission. Finally, the research revealed that the target audience ideology and culture play a crucial in determining the translation strategy to be used.
Abdelaal and Al Sarhani (2021) investigated the strategies used in translating swear words from English into Arabic in the “Training Day” movie and evaluated the subtitling quality. The findings showed that omission and euphemism are the most common strategies employed by the subtitlers. Furthermore, the findings revealed that the translation was of high quality. Similarly, Al-Jabri et al. (2021) examined the strategies used by MBC 4 and Netflix when rendering taboo terms from English to Arabic. In contrast to video streaming services, the researchers assumed that Arabic satellite TV channels experience intervention from religious, political, and social authorities to preserve decent material and censored language in their programs. The study’s results suggested that the Arabic subtitles generated by the satellite Arabic TV channel mainly used euphemistic language. This result is comparable to those made by some researchers who indicated that omission is the most prevalent subtitling strategy in translating swear words and taboos from English into Arabic (Abdelaal and Al Sarhani, 2021; Al-Yasin and Rabab’ah, 2019; Almijrab, 2020; Debbas and Haider, 2020).
The present paper contributes to the previous literature on subtitling swear words by investigating the strategies of subtitling English swear words into Arabic in a large parallel corpus of movies, which consists of forty movies. The study of the subtitling of swear words using a large corpus of movies will likely contribute to the previous literature that investigated a relatively small amount of data. Given the fact that MSA is the Arabic variety that appears on the screen in subtitling, the researchers argue that the degree of offensiveness of swearing will not be maintained in the source text. The investigation of the different Arabic renderings of English swear words may help translators and translation students acquaint themselves with the MSA options that can be used to render swear words using different translation strategies.
Methodology
Why English and Arabic subtitles?
English is the language of most audiovisual products, being the language of communication worldwide (lingua franca). It is the dominant language of communication and is spoken by a huge number of people (Lyons, 2021). According to Al-Zgoul and Al-Salman (2022), Hollywood’s filmmaking companies and the movie industry in the US have a wide reach due to the use of English.
In Arabic-speaking countries, subtitling, rather than dubbing, as an AVT mode is widespread. Movies are subtitled in Modern Standard Arabic (MSA), which is the high variety of Arabic. The use of this variety may reduce the degree of offensiveness when translating culture-bound expressions, including swear words, as MSA is used as a means of euphemism (Haider and Hussein, 2022).
Compared to other AVT modes, such as dubbing, audio description, and voiceover, corpus compilation in subtitling is the easiest, as the data is accessible and available in a written mode. Accordingly, there is no need for transcription, which is demanding, daunting, and time-consuming.
Data selection and corpus compilation
This research is qualitative and quantitative in nature. It uses an English-Arabic parallel corpus comprised of the original scripts of forty English movies and their Arabic subtitles. The movies used in this study were extracted from a larger parallel corpus of movie subtitles titled “English-Arabic Movie Subtitles Corpus (EAMSC) (Abu Rayyash and Haider, 2023). EAMSC is a 1,254,278-word corpus that consists of 70 movie subtitles extracted from Netflix and OSN with an IMDB rating of 8+. The researchers selected the movies that met the following criteria: (a) falling into one of four genres: drama, action, sci-fi, or biography; (b) having a + 8 rating on the IMDB website rating; (c) being translated by Netflix; and d) containing a high frequency of swear words. Forty movies were selected for the purpose of this study, as Table 1 shows.
Table 1. Distribution of movies according to drama, action, sci-fi, and biography genres.
Drama | Action | Sci-Fi | Biography |
|---|---|---|---|
Whiplash | The Dark Knight | Interstellar | The Pianist |
The Martian | The Avengers | Mad Max Fury Road | Rush |
The Father | TYLER the Fellowship of the Ring | V for Vendetta | The Imitation Game |
The Shawshank Redemption | Mosul | Inception | Spotlight |
Gone Girl | Warrior | The Matrix | Into the Wild |
Into the Wild | Batman Begins | Spider-Man: Into the Spider-Verse | The Pursuit of Happiness |
The King’s Speech | The Bourne Ultimatum | Logan | Lion |
There will be Blood | TLOFER the two Towers | Her | A Beautiful Mind |
Shutter Island | Django Unchained | Back to the Future | Goodfellas |
The Wolf of Wall Street | Gladiator | The Prestige | Lawrence of Arabia |
In EAMSC, the English transcription and Arabic subtitles were extracted from Netflix’s official website and opened using Aegisub to make the process of aligning the English dialog with its Arabic counterpart easier since the in-time and out-time are shown, as illustrated in Figs. 1 and 2.
Fig. 1 [Images not available. See PDF.]
The Aegisub file of the English source text extracted from Netflix.
Fig. 2 [Images not available. See PDF.]
The Aegisub file of the Arabic subtitles extracted from Netflix.
The English and Arabic data were copy-pasted to an excel sheet. Each movie is saved in a separate sheet with two columns; the first column contains the English source text, while the second column contains the Arabic subtitles. This step was followed by segmenting and aligning the data. Data segmentation refers to dividing the subtitles into short segments: words, phrases, clauses, and sentences, while data alignment refers to putting the segment in the source text with its equivalent in the target text.
The total word count of the parallel corpus of the current study is 699,229 words comprising 372,071 words for the English sub-corpus and 327,158 words for the Arabic sub-corpus, as Table 2 shows.
Table 2. English-arabic movie subtitles parallel corpus size.
English | 372,071 |
|---|---|
Arabic | 327,158 |
Total | 699,229 |
The parallel corpus is analyzed using SketchEngine, which is a web-based corpus processor developed by Adam Kilgariff (Kilgarriff et al., 2014). Sketch Engine includes some tools such as wordlist, n-gram, concordance, keywords, word sketch, thesaurus, and parallel concordance. In this study, the researchers use the parallel concordance tool to generate concordance lines that include the search term in the two investigated languages (see Al-Khalafat and Haider, 2022).
The researchers can select a query term or search word, which is referred to in the literature as a node word, and Sketch Engine will filter out the English/Arabic lines containing that word, i.e., the source script along with its translation will appear next to each other as Fig. 3 shows.
Fig. 3 [Images not available. See PDF.]
SketchEngine parallel concordance for the word “asshole*“ with the Arabic equivalents.
Adopted translation model in the current study
In this study, we adopt the model proposed by Khoshsaligheh and Ameri (2014), in which the taboo words can be subtitled using one of the following ways:
Taboo-to-Taboo: the swear word in the source text is rendered using an equivalent in the target language (the offensiveness degree and load are maintained).
Taboo-to-non-taboo: the swear word in the source text is neutralized and substituted with a non-taboo expression (neutralization).
Euphemisation/softening: The swear word is translated using a target language euphemistic expression (toning down).
Omission: Not translating the swear word and deleting it in the target language (deletion)
Research procedures
This study follows the following procedures. First, selecting 40 English movies (drama, action, sci-fi, and biography) that have a good number of swear words with a + 8 rating on the IMDB website rating from the “English-Arabic Movie Subtitles Corpus (EAMSC). Second, using SketchEngine to process the data and conduct frequency analysis to identify the ten most frequent words in the corpus. Jay (1992) argued that the most frequently used taboo words are fuck, shit, Jesus/christ, hell, damn, ass, asshole, goddamn/god, bitch, piss, pig, bastard, bullshit, son of a bitch, whore, slut, cock, cocksucker, motherfucker, queer, fag, dick, cunt, pussy, prick, screw, and crap. Similarly, Beers Fägersten (2007) conducted a sociolinguistic analysis of a set of swear words, namely ass, bastard, bitch, cunt, damn, dick, fuck, hell, shit, and their derivatives, e.g., bullshit or Goddamn, which are be the most frequent and common (Jay, 1977, 1980; Johnson and Fine, 1985). If any of these words were among the ten most frequent swear words in the corpus, they would be further analyzed. Third, comparing the frequency of swear words in the four investigated genres. Fourth, using the parallel concordance tool to examine how swear words are rendered in Arabic, categorizing them into three groups, namely omission, softening, and swear-. Fifth, examining the usage of different strategies grouped by swear words.
Analysis and results
Swear words serve as” translation crisis points” since they fall within the category of culture-bound expressions, and rendering them could be very challenging for translators (Pedersen, 2005, p. 1). Khalaf and Rashid (2019) stated that filmmakers purposefully use swear words to reflect the characters’ sociocultural and educational backgrounds and express their inner thoughts. The following sections explore the most frequent swear words in the investigated corpus and examine the strategies used to render them.
Frequency of swear words in the investigated genres
Using the wordlist tool in SketchEngine, the researchers created a frequency analysis for the four sub-corpora to identify the most frequent swear words based on the classification of some researchers (Jay, 1977, 1980, 1992; Johnson and Fine, 1985). In the investigated corpus, the most frequent ten swear words are: fuck, shit, damn, ass, bitch, bastard, asshole, dick, cunt, and pussy, as Table 3 shows.
Table 3. Frequency of swear words along with their derivatives in each genre.
Swear word | Drama | Action | Sci-Fi | Biography | Total |
|---|---|---|---|---|---|
Fuck* | 701 | 50 | 89 | 37 | 877 |
Shit* | 140 | 40 | 60 | 51 | 291 |
Damn | 23 | 30 | 31 | 15 | 99 |
Ass | 24 | 35 | 14 | 20 | 93 |
Bitch* | 21 | 33 | 9 | 12 | 75 |
Bastard* | 5 | 11 | 6 | 12 | 34 |
Asshole* | 17 | 19 | 10 | 11 | 57 |
Dick* | 12 | 2 | 3 | 3 | 20 |
Cunt* | 8 | 3 | 1 | 1 | 13 |
Pussy* | 2 | 1 | 2 | 0 | 5 |
Total | 953 | 224 | 225 | 162 | 1564 |
Wildcards (*) are used to include the term along with its variants. For example, fuck* includes fuck, fucks, fucked, fucking, fucker and motherfucker, among others. Bastard* includes bastard and bastards.
The researchers classified the frequent words found in the corpus based on the categorization of Jay (2009), which includes nine categories, namely, (1) sexual references, (2) profanity or blasphemy, (3) scatological and disgusting objects, (4) animal names, (5) ethnic-racial-gender slurs, (6) psychological-physical-social deviations, (7) ancestral allusions, (8) substandard vulgar terms, and (9) offensive slang. Some words in the investigated corpus contain sexual references, including sexual acts (fuck) and sexual anatomies (dick and cunt). The corpus also contained profane and blasphemous words (e.g., damn), scatological and disgusting objects, including excretion organs (ass and asshole), body products (shit), animal names (bitch and pussy), and ancestral allusions relating to family relationships and ancestors (e.g., bastard).
Table 3 reveals that the total number of hits for the swear word “fuck” along with its derivatives, i.e., fucked, fucking, fuckin, and others, was 877, being the highest when compared with the other words. According to Andersson and Trudgill (1992, p. 60), the word fuck is “one of the most interesting and colorful words in the English language today.” It can be used to describe different emotions, including love, pleasure, hatred, and pain (McEnery and Xiao, 2004).In addition, the f-words have cultural and social interpretations and are part of the dramatic plot in various movie genres. According to Pujol (2006), the word “fuck” is employed in movies to communicate severe wrath, emphasis, disgust, disdain, surprise, and delight, pointing out that these categories are not exhaustive and sometimes overlap. The word “shit” was the second most frequently used swear word in the data, with 291 hits. Kristiano and Ardi (2018) conducted a semantic analysis of the swear words in Bad Boys II and found that the word shit was the most frequent swear word in the movie, followed by fuck. The frequency of each of the remaining swear words did not exceed 100 hits.
It is worth noting that the intensity of offensiveness varies based on the word used. Beers Fägersten (2007, p. 5) argued that “certain swear words are consistently rated more offensive than others, with sexual terms receiving higher offensiveness scores than excretory/body and sacred terms.” For example, swear words like fuck and motherfucker are rated higher than ass, asshole, and shit. These are rated higher than hell, and damn. It is worth noting that dick and cunt received a high offensive rating. According to (Ljung, 2011, p. 9), “the BBC guidelines do mention the three words considered most offensive, viz. cunt, fuck, and motherfucker”. The investigated words in this study can be rated from the most offensive to the least as cunt, fuck (including motherfucker), bitch, asshole, bastard, pussy, dick, ass, shit, and damn.
Swear words were used the most in drama movies, with a percentage of 61%, followed by action and sci-fi with 14% for each, and biography (11%), as Fig. 4 shows.
Fig. 4 [Images not available. See PDF.]
Swear words in the four investigated movie genres.
Clearly, the drama genre has the lion’s share in the use of swear words by more than half of the total hits of the other movies collectively. Adriani and Hamzah (2013, p. 72) stated that “Drama Movie is a genre of movies with serious presentations or stories with settings or life situations that portray realistic characters in conflict with either themselves, others, or forces of nature.” Therefore, the dramatic elements in the plot can be reflected in the frequent inclusion of swear words that serve as a populist reservoir of language. This can help convey ideas and emotions more effectively.
Translation strategies used in rendering swear words
Omission
Omission is a strategy where the translator deletes part of the expression or leaves it out fully. It is one of the most common practices in translation, especially when the translator fails to render the source language expression due to temporal, spatial, or cultural constraints. In this study, subtitlers resorted to this strategy the most. This could be due to the strict censorship policies and cultural constraints that subtitlers should abide by. Table 4 shows the number of instances in which the subtitler omitted the swear word.
Table 4. Number and percentage of using omission in the four investigated genres.
Swear word | Drama | Action | Sci-Fi | Biography | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
Total | Omi. | % | Total | Omi. | % | Total | Omi. | % | Total | Omi. | % | |
Fuck | 692 | 506 | 73% | 59 | 23 | 39% | 89 | 38 | 43% | 37 | 22 | 59% |
Shit | 134 | 94 | 70% | 45 | 29 | 64% | 60 | 20 | 33% | 51 | 30 | 59% |
Damn | 22 | 10 | 45% | 30 | 24 | 80% | 31 | 17 | 55% | 15 | 10 | 67% |
Ass | 24 | 18 | 75% | 35 | 31 | 89% | 14 | 12 | 86% | 20 | 11 | 55% |
Bitch | 31 | 0 | 0% | 25 | 22 | 88% | 9 | 1 | 11% | 6 | 6 | 100% |
Bastard | 7 | 0 | 0% | 12 | 0 | 0% | 6 | 1 | 17% | 12 | 3 | 25% |
Asshole | 17 | 0 | 0% | 12 | 7 | 58% | 10 | 0 | 0% | 17 | 2 | 12% |
Dick | 12 | 5 | 42% | 2 | 0 | 0% | 3 | 1 | 33% | 3 | 0 | 0% |
Cunt | 9 | 0 | 0% | 3 | 0 | 0% | 1 | 0 | 0% | 1 | 0 | 0% |
Pussy | 5 | 0 | 0% | 1 | 0 | 0% | 2 | 0 | 0% | 0 | 0 | 0% |
Total | 953 | 633 | 66% | 224 | 136 | 61% | 225 | 90 | 40% | 162 | 84 | 52% |
Table 4 shows that omission was the most used strategy in rendering swear words in drama movies, with 633 hits (66%), followed by action movies (61%), sci-Fi (40%), and biography (52%). Additionally, Table 4 shows that the deletion of words varies from one swear word to another. For example, in drama movies, the swear words “ass,” “fuck,” and “shit” were the most omitted words, with (75), (73), and (73%) respectively. In drama movies, the subtitlers did not resort to the translation strategy of omission in rendering the swear words cunt, bitch, asshole, bastard, and “pussy”. These words, especially “cunt” have high offensiveness scores and can be omitted rather than softened or substituted. The frequency of these words in Drama movies is 69, which is relatively low when compared to the other five investigated words. It can also be observed that in the four investigated genres, the subtitlers did not use the strategy of “omission” in translating the swear words “cunt” and “pussy”.
The choice of omission may depend on the function of the swear words in the utterance, i.e., whether they are interjections (e.g., Shit! Fuck!) and mainly used to express the speakers’ reactions including anger, surprise, pain, and other feelings, emphasizers (e.g., what the hell is the matter?”, or slot fillers (e.g., bloody fool), or replacive (Ljung, 2011).
As stated before, omission is the act of dropping a word from the target language while translating. The cultural variations between the SL and TL may necessitate applying omission in order to escape a potential cultural predicament. Resorting to omission is commonly used in subtitling when compared to other translation modes. This study revealed that subtitlers’ omission is the most frequently employed strategy when rendering swear words from English into Arabic. The subtitlers may omit swear words that have no equivalents in the target language or elicit negative reactions from the audience. According to Abdelaal and Al Sarhani (2021), omission can be used due to constraints in the target culture, making it tough to render some swear words into Arabic, particularly those that are considered highly derogatory and abhorrent. Another reason for adopting this strategy in subtitling is spatial constraints, which allow for a limited number of characters. Table 5 shows some examples of how this strategy was used in the data.
Table 5. Examples of ST swear words and their TT omission.
Genre | No. | ST | TT | Back Translation | Comment |
|---|---|---|---|---|---|
Drama | 1 | A thousand plants with thorns as big as my dick. | آلاف النباتات ذات الأشواك الضخمة. | A thousand plants with thorns. | The entire phrase, including the swear word “as big as my dick,” was deleted. |
2 | You are fucking kidding me. | أنت تمزح معي. | You are kidding me. | “fucking” was deleted, and its function was not regenerated | |
Action | 3 | Don’t throw another fucking grenade! | لا ترموا قنبلة أخرى! | Don’t throw another grenade! | “fucking” was deleted, and its function was not regenerated |
4 | Those was all the beat ass niggers I wanna sell. | وهؤلاء الزنوج الذين أريد بيعهم. | Those were all the niggers I wanna sell. | “beat ass” was deleted, and its function was not regenerated | |
Sci-fi | 5 | Find a gear, dumb ass. Grind it! | عشقيه جيدا. إنه يجرش. | Find a gear. Grind it! | “dumb ass” was deleted, and its function was not regenerated |
6 | Cooper, it’s too damn fast! I got this. | السرعة كبيرة. سأتولى الأمر. | It’s too fast! I got this. | “damn” was deleted, and its function was not regenerated | |
Biography | 7 | Shut your ass up, man, and leave me alone! | اخرس يا رجل، دعني وشأني. | Shut up, man, and leave me alone! | “ass” was deleted, and its function was not regenerated |
8 | I got three of them before the damn office is even open. | لدي ثلاثة مواعيد عمل قبل فتح المكتب. | I got three of them before the office was even open. | “damn” was deleted, and its function was not regenerated |
As Table 5 shows, the ST swear words “dick,” “fucking”, “damn,” and “ass” were omitted from the subtitles. When resorting to this strategy, the “connotative” function of swear words is not maintained, and the sentence’s overall meaning is affected. According to Al-Yasin and Rabab’ah (2019, p. 22), this may result “into missing the pragmatic function of the utterance since the occurrence of the taboo word may indicate a certain feeling like anger or surprise.” Hendal (2021) stated that the omission strategy might not alter the original meaning but instead remove the author’s sentiments. Hence, rendering swear words using the omission strategy leads to the neglect of the feelings involved in the screenplay, as illustrated in the above examples. This is supported by Al-Adwan and Yahiaoui (2018, p. 88) who argue that “modifying or cutting parts of the original contents of foreign films would affect the experience of the Arab audience and present to them an altered representation of the original plot and characters”.
Softening
The subtitlers use the softening strategy as it relatively satisfies the viewers of the conservative target culture without much neglect of the linguistic function of the swear words. Softening refers to the translation of the ST swear word by using a TL swear word that is gentler or milder in tone (Díaz-Pérez, 2020). Professional subtitlers had little choice but to hold the stick in mid-air to avoid falling prey to the critic’s hammer when rendering the swear words. Table 6 summarizes the distribution of the softening strategy in the investigated genres.
Table 6. Total number and percentage of softening strategy in the four investigated movie genres.
Swear word | Drama | Action | Sci-Fi | Biography | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
Total | Soft. | % | Total | Soft. | % | Total | Soft. | % | Total | Soft. | % | |
Fuck | 692 | 108 | 16% | 59 | 20 | 34% | 89 | 33 | 37% | 37 | 9 | 24% |
Shit | 134 | 32 | 24% | 45 | 9 | 20% | 60 | 26 | 43% | 51 | 13 | 25% |
Damn | 22 | 9 | 41% | 30 | 4 | 13% | 31 | 9 | 29% | 15 | 3 | 20% |
Ass | 24 | 4 | 17% | 35 | 3 | 9% | 14 | 1 | 7% | 20 | 6 | 30% |
Bitch | 31 | 13 | 42% | 25 | 8 | 32% | 9 | 6 | 67% | 6 | 5 | 83% |
Bastard | 7 | 3 | 43% | 12 | 7 | 58% | 6 | 3 | 50% | 12 | 6 | 50% |
Asshole | 17 | 9 | 53% | 12 | 8 | 67% | 10 | 5 | 50% | 17 | 7 | 41% |
Dick | 12 | 5 | 42% | 2 | 1 | 50% | 3 | 1 | 33% | 3 | 2 | 67% |
Cunt | 9 | 5 | 56% | 3 | 2 | 67% | 1 | 1 | 100% | 1 | 1 | 100% |
Pussy | 5 | 1 | 20% | 1 | 1 | 100% | 2 | 2 | 100% | 0 | 0 | 0% |
Total | 953 | 189 | 20% | 224 | 63 | 28% | 225 | 87 | 39% | 162 | 51 | 32% |
Table 6 shows that the softening strategy was most observed in sci-fi movies (39%) and least used in drama movies (20%). Some examples of this strategy are shown in Table 7.
Table 7. Examples of ST swear words and their TT equivalence.
Genre | No. | ST | TT | Back translation | Comment |
|---|---|---|---|---|---|
Drama | 9 | Spoiled rich girl, married a cheating asshole. | فتاة ثرية مدللة، تزوجت وغدا خائنا. | Spoiled rich girl married a cheating rogue. | The Arabic word وغد is used to describe a dishonest, unscrupulous, or unprincipled person. |
10 | Bitch had a foot fetish or something. | كان لدى السافلة هوس بالقدم أو ما شابه. | The immoral woman had a foot fetish or something. | The Arabic word سافل is used to describe vile, lowly, and lousy people. | |
Action | 11 | You dumb bitch. | أيتها الشريرة الغبية! | You dumb evil. | The English word bitch was translated into Arabic as شريرة, which is used to describe a person who is profoundly immoral and wicked. |
12 | And the dicks responsible. | والأوغاد المسؤولين عن ذلك. | And the rogue responsible. | The Arabic word وغد is used to describe a dishonest, unscrupulous, or unprincipled person. | |
13 | Don’t ‘who’ me bitch, you know who I’m talking about!? | بدون “من“ أيتها الفاجرة، تعرفين جيدا من اقصد. | Don’t ‘who’ me whore. You know who I’m talking about. | The Arabic word فاجرة is used to describe a person who has unlawful sexual intercourse as or with a prostitute | |
Sci-fi | 14 | I’m such an asshole. | أنا مغفلة جدا. | I’m such a stupid. | “Asshole” was rendered as مغفل which is used to describe fool or stupid people. |
15 | Waste this dick, Logan! | اقض على هذا الوغد يا “لوغان“! | Waste this rogue, Logan! | The Arabic word وغد is used to describe a dishonest, unscrupulous, or unprincipled person. | |
16 | I’m a bitch. | أنا سافلة. | I’m an immoral woman. | The Arabic word سافل is used to describe vile, lowly, and lousy people. | |
Biography | 17 | Is my roommate a dick? | هل شريكي بالغرفة أحمق؟ | Is my roommate stupid? | Dick was translated as أحمق which is used in Arabic to describe foolish, silly or senseless people |
18 | Son of a bitch. | ابن العاهرة | Son of a bitch. | The Arabic word عاهرة is used to describe female prostitute who engages in sex acts for money. |
Table 7 shows that the Arabic word “وغد rogue” was the most used by the subtitlers in rendering various swear words such as “asshole” (example 9) and “dick” (examples 12 and 15). While the swear word “bitch” was translated using the swear words “سافلة“, “عاهرة“ and “فاجرة,” all of which include the Arabic feminine marker. As discussed before, the subtitles are written in Modern Standard Arabic (MSA) rather than vernaculars, with the former being a vehicle of polite language and does not use impolite terms, while the latter associating with lowly and nonprestigious functions, vulgarisms, and obscene words. According to Haider and Hussein (2022, p. 3), “words tend to be formal and polite in MSA, while their equivalents in colloquial lack this attribute.” Words like وغد rogue and سافل immoral/scummy are offensive words in Arabic. However, they are not as offensive as the English words, most likely because of the used variety of Arabic in the subtitles. Based on this, it can be argued that the use of some equivalent terms in Arabic, like عاهرة bitch would more directly translate the original English terms when compared to other equivalents, such as سافلة immoral.
Since subtitlers are aware that SL swear words are undesirable to TL individuals and society, they choose to tone them down. Resorting to this strategy gives the subtitlers more freedom to interpret the meaning in the cinematic dialog. Thus, the subtitlers succeeded to some extent in softening the swear words and mitigating their impact on the viewer in a way that preserved the general meaning of these words.
Swear to non-Swear
This strategy indicates turning the SL swear word into a TL non-swear word that has a neutral emotive meaning (Díaz-Pérez, 2020). Swear-to-non-swear, or taboo-for-non-taboo translation, occurs when the translated text is neutralized. Table 8 summarizes the distribution of the swear-to-non-swear strategy in the investigated genres.
Table 8. Total number and percentage of swear-to-non-swear strategy in four investigated movie genres.
Swear word | Drama | Action | Sci-Fi | Biography | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
Total | S. to Non-S. | % | Total | S. to Non-S. | % | Total | S. to Non-S. | % | Total | S. to Non-S. | % | |
Fuck | 692 | 87 | 13% | 59 | 7 | 12% | 89 | 18 | 20% | 37 | 6 | 16% |
Shit | 134 | 14 | 10% | 45 | 2 | 4% | 60 | 14 | 23% | 51 | 8 | 16% |
Damn | 22 | 4 | 18% | 30 | 2 | 7% | 31 | 5 | 16% | 15 | 2 | 13% |
Ass | 24 | 2 | 8% | 35 | 1 | 3% | 14 | 1 | 7% | 20 | 3 | 15% |
Bitch | 31 | 8 | 26% | 25 | 3 | 12% | 9 | 2 | 22% | 6 | 1 | 17% |
Bastard | 7 | 2 | 29% | 12 | 4 | 33% | 6 | 2 | 33% | 12 | 3 | 25% |
Asshole | 17 | 8 | 47% | 12 | 4 | 33% | 10 | 5 | 50% | 17 | 2 | 12% |
Dick | 12 | 2 | 17% | 2 | 1 | 50% | 3 | 1 | 33% | 3 | 1 | 33% |
Cunt | 9 | 3 | 33% | 3 | 1 | 33% | 1 | 0 | 0% | 1 | 0 | 0% |
Pussy | 5 | 1 | 20% | 1 | 0 | 0% | 2 | 0 | 0% | 0 | 0 | 0% |
Total | 953 | 131 | 14% | 224 | 25 | 11% | 225 | 48 | 21% | 162 | 26 | 16% |
Table 8 shows that the softening strategy was most observed in sci-fi movies (21%) and least used in action movies (11%). Table 8 indicates the number and percentage of using the swear-to-non-swear strategy in the investigated four movie genres. The data shows that the number of swear words rendered using the swear-to-non-swear strategy was most used in the drama genre with 131 hits, followed by the sci-fi genre with 45 hits, biography (26 hits), and finally action (25 hits). Some examples of this strategy are shown in Table 9.
Table 9. Examples of ST swear words and their TT non-swear counterparts.
Genre | No. | ST | TT | Back translation | Comment |
|---|---|---|---|---|---|
Drama | 19 | Damn, right we’re gonna run it. | سننشرها بكل تأكيد | Sure, we’re gonna run it. | The word damn was rendered asبكل تأكيدsure |
20 | When I see you, you’d treat me like shit. | وستعاملني بطريقة سيئة عند ما أراك. | When I see you, You’d treat me in a bad way. | The word shit was rendered as بطريقة سيئة a bad way | |
21 | She’s got an ass like a 22-year-old stripper. | وكان جسدها جميلا للغاية. | She’s got a body like a 22-year-old stripper. | The word ass was rendered using a more general word which is جسد body | |
Action | 22 | Very funny, bitch. | أنت مضحكة للغاية. | You are very funny. | “Bitch” was deleted and substituted with انت “you” |
23 | Okay, start the bastard. | حسنا، قم بتشغيل السيارة. | Okay, start the car. | “Bastard” was deleted and substituted with سيارة “car” | |
Sci-fi | 24 | It takes two numbers to measure your ass but only one to measure my son’s future? | برقمين تقيس سروالك وبواحد تقيس مستقبل ابني؟ | It takes two numbers to measure your trouser but only one to measure my son’s future? | “Ass” was deleted and substituted with سروال “trouser.” |
25 | I can’t believe you watch that shit. | لا يمكنني أن أصدق أنك تشاهد هذه الرداءة. | I can’t believe you watch that bad thing. | “shit” was deleted and substituted with رديء “bad.” | |
Biography | 26 | Whole thing was, uh, over a piece of ass, right? | كل شيء كان بسبب فتاة، أليس كذلك؟ | The whole thing was, uh, over a girl, right? | “Ass” was deleted and substituted with فتاة “girl.” |
27 | Wait a minute. You’re full of shit. | انتظر دقيقة. أنت مليء بالكذب. | Wait a minute. You’re full of lies. | “shit” was deleted and substituted with كذب “lies.” |
Table 9 shows examples of the swear-to-non-swear strategy where the English swear words were substituted with Arabic non-swear words. In some incidents, the function of the swear words in the English text is replacive, where they replace a lexical item. In rendering swear words with this function, the subtitlers used the replaced lexical item to make the context clearer for the audience. In example 23, which reads “start the bastard,” the subtitler replaced bastard with سيارة car. According to Al-Zgoul and Al-Salman (2022) replacive swearing plays a role in building the context. In example 21, the swear word “ass” was substituted with a more general word, “body,” while in example 26, the same word was replaced with “a girl.”
Table 10 shows the number of occurrences and the percentage of each subtitling strategy used to render swear words from English into Arabic in the four investigated movie genres, namely, drama, action, sci-fi, and biography.
Table 10. Total frequency of subtitling strategies in the four different movie genres.
Movie genre | Omission | Softening | Swear-to-non-swear | Total | ||||
|---|---|---|---|---|---|---|---|---|
Frequency | % | Frequency | % | Frequency | % | |||
Drama | 633 | 66% | 189 | 20% | 131 | 14% | 953 | 100% |
Action | 136 | 61% | 63 | 28% | 25 | 11% | 224 | 100% |
Sci-Fi | 90 | 40% | 87 | 39% | 48 | 21% | 225 | 100% |
Biography | 84 | 52% | 52 | 32% | 26 | 16% | 162 | 100% |
Total | 943 | 60% | 390 | 25% | 230 | 15% | 1564 | 100% |
As can be observed from the data, the omission strategy accounted for the lion’s share in the number of swear words in all the different genres mentioned, with 66% for drama, 61% for action, 40% for sci-fi, and 52% for biography. On the other hand, the softening strategy got the second-highest frequencies across the different movie genres, with 39% for sci-fi, 32% for biography, 28% for action, and 20 for drama. In addition, the swear-to-non-swear strategy was the least often adopted by subtitlers in rendering swear words from English into Arabic, accounting for 21% for sci-fi, 16% for biography, 14% for drama, and 11% for action (see Fig. 5).
Fig. 5 [Images not available. See PDF.]
Translation strategies in the four investigated genres.
The strategy of omission was used in about two-third of the swear words as Fig. 5 shows. This strategy could be the easiest for the subtitlers, as it does not require any effort from the subtitlers. However, using it densely may affect the meaning and sometimes lead to poor translation (Al-Zgoul and Al-Salman, 2022). It can be argued that omission occurred due to technical or cultural constraints, with the former relating to the spatial and temporal aspects of the subtitles and the latter to the differences between liberal and conservative cultures. Antonini (2005) argued that omission is a reduction strategy resulting from the technical constraints of time and space. However, the meaning of the audiovisual product should be delivered with such technical constraints (Matkivska, 2014). Resorting to the strategy of omission seems to be relatively common, as it was discussed by different scholars (ElShiekh, 2016; Hosseinnia, 2014; Simanjuntak and Basari, 2016). Using this strategy is not haphazard and requires a profound knowledge of the connotative functions of the linguistic elements so that susbtitlers compensate for the loss that occurred due to the act of deletion. To reflect and recap, omission affects utterances due to what Matkivska (2014) explained as the synchronism of the characteristic, which entails delivering the meaning of the whole audiovisual product within the technical constraints. The other two strategies that were used by the subtitlers are softening (euphemism) and swear-to-non-swear (neutralization). These two strategies could be better choices when compared to omission, as the loss of the meaning resulting from the deletion of the swear words may affect the comprehension of the target audience. The findings of this study are in harmony with those of Cuenca (2016) who examined the strategies used in subtitling taboo words from English into Spanish and found that omission, euphemism, and neutralization were employed by the subtitlers.
As mentioned before, ten swear words were spotted to be further investigated. These included fuck, shit, damn, ass, bitch, bastard, asshole, dick, cunt, and pussy. Table 11 shows the usage of different strategies, grouped by swear words.
Table 11. Total hits of each swear word using the three strategies.
Swear word | Omission | % | Softening | % | Swear-to-non-Swear | % | Total hits |
|---|---|---|---|---|---|---|---|
Fuck | 589 | 67% | 170 | 19% | 118 | 14% | 877 |
Shit | 173 | 60% | 80 | 27% | 38 | 13% | 291 |
Damn | 61 | 62% | 25 | 25% | 13 | 13% | 99 |
Ass | 72 | 77% | 14 | 15% | 7 | 8% | 93 |
Bitch | 29 | 38% | 32 | 43% | 14 | 19% | 75 |
Bastard | 4 | 12% | 19 | 56% | 11 | 32% | 34 |
Asshole | 9 | 16% | 29 | 51% | 19 | 33% | 57 |
Dick | 6 | 30% | 9 | 45% | 5 | 25% | 20 |
Cunt | 0 | 0% | 9 | 69% | 4 | 31% | 13 |
Pussy | 0 | 0% | 4 | 80% | 1 | 20% | 5 |
Total | 943 | 60% | 391 | 25% | 230 | 15% | 1564 |
Omission was the most used translation strategy in rendering the words fuck, shit, damn, and ass; softening was used primarily in translating the words pussy, cunt, bastard, asshole, dick, and bitch. Swear-to-non-swear was mainly used with the swear words asshole, bastard, and cunt. The strength and offensiveness of the investigated swear words are discussed. On this basis, ‘stronger’ swear words would invite different strategies, i.e., strong swear words would be omitted, while less offensive words would be softened or substituted. The investigated words in this study can be rated from the most offensive to the least as cunt, fuck (including motherfucker), bitch, asshole, bastard, pussy, dick, ass, shit, and damn. However, as argued above, with the use of the MSA variety of Arabic, these words would lose their strength or offensiveness. Accordingly, the level of offensiveness in the source text is not maintained in the target text.
To help subtitlers, translation students and translation training programs render the ten swear words investigated in this study into Arabic, the researchers summarized the most frequent Arabic translations of these words. The swear words are sometimes rendered literally in a euphemistic way; for example, the word fuck was rendered as يضاجع get laid/make love 24 times. However, other times, they are used connotatively. For example, the Arabic word تبا (Lit. doom and lose) was used 163 times to render the words fuck (92 times), shit (60), and damn (11). Give a damn/fuck was mainly rendered using the euphemistic expressions يأبه، يعبأ، يهتم، يبالي, meaning care. Similarly, the word اللعنة (Lit. curse) was the most frequently used in translating English swear words, where it is used 118 times to render the words fuck, shit, and damn. Arabic epithets like احمق fool (5 times), أخرق clumsy (5 times), حثالة scum (22), حقير despicable (19 times), قذر nasty (19 times), وضيع lowly (3 times), غبي stupid (3 times), نذل villain (4 times) and وغد nasty (16 times). Some tense Arabic attributes were also observed in the data, such as داعر sluttish, داعرة whore, سافل bastard, سافلة Bitch, ساقطة Bitch, عاهرة whore, فاجرة whore, and لقيط bastard. Some euphemistic expressions to refer to body organs were frequently used, such as العضو الأنثوي التناسلي female genital organ, المنطقة الخاصة private area, أعضاء تناسلية genitals, جسد body, عضو organ, رجولة manhood, and مؤخرة butt. Other times, literal translation was used to render some words like قضيب dick.
Conclusion
This study combines corpus linguistics and audiovisual translation to examine the translation strategies adopted by Netflix subtitlers in rendering swear words in 40 English movies into Arabic. Swear words express the speaker’s sentiments and reactions in an impolite manner (Moore, 2012). Swear words can be observed frequently in some movies. Various genres, such as drama, action, and comedy, to mention a few, include different swear words to convey some messages in a particular way. The translation of swear words is a subject of contention among translators and researchers, especially if the target culture is conservative. Ten swear words, namely fuck, shit, damn, ass, bitch, bastard, asshole, dick, cunt, and pussy were frequently observed in the data. Going through the data and comparing the English swear words with their Arabic equivalents, the researchers classified the strategies of rendering swear words into three categories: omitting the ST swear words from the target text, rendering ST swear words into TT non-swear words, and softening the ST swear words. The analysis showed that omission is the most frequently used strategy by professional subtitlers in rendering English swear words into Arabic.
While the results obtained in the current study are aligned with the research questions, there have been some limitations and recommendations. The current study’s data were retrieved from Netflix; future studies may investigate fansubbing as they are abundantly available via different websites1. Future research can also bulid on the few studies that investigated subtitles of prominnat satellite channels in the Arab World (see Al-Adwan, 2019; Al-Jaberi et al., 2021). This study was conducted on four movie genres, as the other genres are not available in abundance compared to drama, action, sci-fi, and biography on the one hand, and their inclusion of plenty of swear words on the other hand. Other genres can be the data source for future studies.
This study uses a parallel corpus of English-Arabic movie subtitles and recommends more corpus-assisted studies on different AVT modes, including dubbing, voiceover, and free commentaries. Furthermore, the researchers recommend more AVT research on swear words in different languages, as they represent a controversial issue, especially when translating for conservative cultures. This study investigated a large chunk of data quantitatively; other studies may attempt to identify fansubbing norms in a limited number of movies as this may allow them to examine them in detail. This study was limited to translation strategies; other studies may examine the denotative and connotative functions of swear words and the typology of swearing.
To conclude, further research on the different AVT modes is needed to help translators identify the best and most appropriate strategies to opt for when rendering culture-bound expressions, including swearing. Such research will significantly help subtitlers, translation students, and translation training programs.
Funding
Open Access funding provided by the Qatar National Library.
Data availability
The data are available on request from the authors.
Competing interests
The authors declare no competing interests.
Ethical approval
This article does not contain any studies with human participants performed by any of the authors.
Informed consent
This article does not contain any studies with human participants performed by any of the authors.
1Such as www.subscene.com.
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
References
Abdelaal, NM; Al Sarhani, A. Subtitling strategies of swear words and taboo expressions in the movie “Training Day”. Heliyon; 2021; 7,
Abu Rayyash H, Haider AS (2022) Construction of a parallel corpus of English-Arabic movie subtitles: a genuine source for audiovisual translators. The International Journal of Humanities Education 21(1): 21–37. https://doi.org/10.18848/2327-0063/CGP/v21i01/21-37
Adriani, KGD; Hamzah, HA. Comparison of the maxim violation found in action and drama movies. Engl Lang Lit; 2013; 1,
Al-Abbas, LS; Haider, AS. Using modern standard arabic in subtitling egyptian comedy movies for the deaf/hard of hearing. Cogent Arts Humanit; 2021; 8,
Al-Adwan, A. Said Faiq,. Mapping arabic subtitling conventions: the case of Dubai one and MBC 2. Arabic Transl Across Discourse; 2019; London, Routledge: pp. 63-78. [DOI: https://dx.doi.org/10.4324/9781351063388-5]
Al-Adwan, A; Yahiaoui, R. Irene, R; Serenella, Z. Comedy under fire: subtitling Two and a Half Men into Arabic. Linguistic and cultural representation in audiovisual translation; 2018; Lonodn/New York, Rourteldge: pp. 85-100. [DOI: https://dx.doi.org/10.4324/9781315268552-6]
Al-Jabri, H; Allawzi, A; Abushmaes, A. A comparison of euphemistic strategies applied by Mbc4 and netflix to two arabic subtitled versions of The US sitcom how i met your mother. Heliyon; 2021; 7,
Al-Khalafat, L; Haider, AS. A corpus-assisted translation study of strategies used in rendering culture-bound expressions in the speeches of King Abdullah II. Theory Pract Lang Stud; 2022; 12,
Al-Yasin, NF; Rabab’ah, GA. Arabic audiovisual translation of taboo words in American hip hop movies: a contrastive study. Babel; 2019; 65,
Al-Zgoul, O; Al-Salman, S. Fansubbers’ subtitling strategies of swear words from English into Arabic in the bad boys movies. Open Cult Stud; 2022; 6,
Alabbasi, A. Omar, HC. Translation (Arabic-English). The sustainability of the translation field; 2009; Malaysia, ITBM: 179.
Allan, K. When is a slur not a slur? The use of nigger in ‘Pulp Fiction’. Lang Sci; 2015; 52, pp. 187-199. [DOI: https://dx.doi.org/10.1016/j.langsci.2015.03.001]
Almijrab, R. Strategies used in translating English taboo expressions into Arabic. African J Soc Sci Humanit Res; 2020; 3,
Alsharhan, A. Netflix’s no-censorship policy in subtitling taboo language from English into Arabic. J Audiovis Transl; 2020; 3,
Ameri, S; Ghazizadeh, K. A norm-based analysis of swearing rendition in professional dubbing and non-professional subtitling from English into Persian. Res English Lang Pedagogy; 2014; 2,
Andersson, L; Trudgill, P. Bad language; 1992; London, Penguin Books:
Anthony, L. AntConc (Version 3.2.5); 2013; Tokyo, Japan, Waseda University:
Antonini, R. The perception of subtitled humor in Italy. Humor; 2005; 18,
Aqel, YAA. Constraints on translating taboo language in English movies into Arabic. (Master Degree); 2016; Palestine, An-Najah National University:
Au, K. Fong, G; Au, K. Introduction. Dubbing and subtitling in a world context; 2009; Hong Kong, Chinese University Press: pp. 7-12.
Baker, M. Baker, M; Francis, G; Tognini-Bonellis, E. Corpus linguistics and translation studies: implications and applications. Text and technology: in honor of John Sinclair. Text and technology: in honor of John Sinclair; 1993; Amsterdam, John Benjamins Publ: pp. 233-250. [DOI: https://dx.doi.org/10.1075/z.64.15bak]
Beers Fägersten K (2007) A sociolinguistic analysis of swear word offensiveness. Saarland Working Papers in Linguistics. Universität des Saarlands
Chaume, F. Audiovisual translation: dubbing; 2020; London, Routledge: [DOI: https://dx.doi.org/10.4324/9781003161660]
Chen, C. On the Hong Kong Chinese subtitling of english swearwords. Meta: J Des Traducteurs/Meta: Translators’ J; 2004; 49,
Crane, LB; Yeager, E; Whitman, RL. An introduction to linguistics; 1981; United States, Little, Brown:
Cuenca, A. On the translation of taboo words in an English-Spanish corpus of film subtitles. (Unpublished doctoral dissertation); 2016; Spain, UNIVERSIDAD DE JAÉN:
Debbas, M; Haider, AS. Overcoming cultural constraints in translating English series: a case study of subtitling family guy into Arabic. 3L: Lang Linguist Lit®; 2020; 26,
Dewaele, J-M. The emotional force of swearwords and taboo words in the speech of multilinguals. J Multiling Multicult Dev; 2004; 25,
Díaz-Cintas, J; Muñoz Sánchez, P. Fansubs: audiovisual translation in an amateur environment. Jostrans; 2006; 6, pp. 37-52.
Díaz-Cintas, J; Remael, A. Audiovisual translation: subtitling; 2014; London & New York, Routledge: [DOI: https://dx.doi.org/10.4324/9781315759678]
Díaz-Pérez, FJ. Translating swear words from English into Galician in film subtitles: a corpus-based study. Babel; 2020; 66,
Dynel, M. Swearing methodologically: The (im) politeness of expletives in anonymous commentaries on YouTube. J Engl Stud; 2012; 10, pp. 25-50. [DOI: https://dx.doi.org/10.18172/jes.179]
ElShiekh, A. Problems in English to Arabic subtitles translation of religious terms-bruce almighty and supernatural on MBC & Dubai one: a case study. Int J Engl Linguist; 2016; 6,
Farghal M (1995) Euphemism in Arabic: a gricean interpretation. Anthropol Linguist 37: 366–378.
Fernández, MJF. Díaz-Cintas, J. The translation of swearing in the dubbing of the film South Park into Spanish. New trends in audiovisual translation; 2009; United Kindom, Multilingual Matters: pp. 210-225. [DOI: https://dx.doi.org/10.21832/9781847691552-017]
Goddard, C. “Swear words” and “curse words” in Australian (and American) English. At the crossroads of pragmatics, semantics and sociolinguistics. Intercult Pragmat; 2015; 12,
Gottlieb, H. García, L; Rodriguez, A. Subtitling: visualising filmic dialogue. Traducción subordinada (II). El subtitulado (inglés-español/galego); 2001; Spain, Servicio de publicacións da Universidade de Vigo: pp. 85-110.
Hagen, SH. Swearwords and attitude change: a sociolinguistic study; 2013; Norway, The University of Bergen:
Haider AS, Al-Saideen B, Hussein RF (2023) Subtitling taboo expressions from a conservative to a more liberal culture: the case of the Arab TV series ‘Jinn’. Middle East J Cult Commun (in press)
Haider AS, Hussein RF (2022) Modern standard Arabic as a means of euphemism: a case study of the MSA intralingual subtitling of jinn series. J Intercult Commun Res Online First, 1–16. https://doi.org/10.1080/17475759.2022.2106289
Hendal, B. Translation of taboos: a case study on translating the F-word into Arabic. J Res Lang Transl; 2021; 1,
Hosseinnia, M. Omission as a strategy in subtitling. Int J Lang Learn Appl Linguist World; 2014; 5,
House, J. A model for assessing translation quality. Meta: journal des traducteurs/Meta: Translators’ Journal; 1977; 22,
Ivarsson, J; Crofts, RF. Subtitling for the media: a handbook of an Art; 1992; Sweden, Transedit:
Jay, T. Doing research with dirty words. Maledicta: Int J Verb Aggress; 1977; 1,
Jay T (1980) A frequency count of college and elementary school students’ colloquial English. Catal Sel Doc Psychol 10(1). https://doi.org/10.1037/e481592008-001
Jay, T. Cursing in America: a psycholinguistic study of dirty language in the courts, in the movies, in the schoolyards, and on the streets; 1992; Amsterdam, John Benjamins Publishing: [DOI: https://dx.doi.org/10.1075/z.57]
Jay, T. The utility and ubiquity of taboo words. Perspect Psychol Sci; 2009; 4,
Jay, T; Janschewitz, K. The pragmatics of swearing. J Politeness Res; 2008; 4,
Johnson, FL; Fine, MG. Sex differences in uses and perceptions of obscenity. Women’s Stud Commun; 1985; 8,
Karamitroglou, F. Towards a methodology for the investigation of norms in audiovisual translation: The choice between subtitling and revoicing in Greece (Vol. 15); 2000; Amsterdam, Rodopi: [DOI: https://dx.doi.org/10.1163/9789004485891]
Khalaf, AS; Rashid, SM. Pragmatic functions of swearwords in the amateur subtitling of American crime drama movies into Arabic. Int J Asia-Pacific Stud; 2019; 15,
Khoshsaligheh, M; Ameri, S. Translation of taboos in dubbed American crime movies into Persian. T&I Rev; 2014; 4,
Kilgarriff, A; Baisa, V; Bušta, J; Jakubíček, M; Kovář, V; Michelfeit, J; Suchomel, V. The sketch engine: ten years on. Lexicography; 2014; 1,
Krishan, T. Norms of subtitling taboo language and the role of censorship in Jordan: a case study of the Arabic subtitling of’Friends’; 2012; United Kingdom, (Ph.D.), University of Salford:
Kristiano, JT; Ardi, P. Swear words in Bad Boys II: a semantic analysis. LLT J; 2018; 21,
Kruger, A; Wallmach, K; Munday, J. Corpus-based translation studies: Res Appl; 2011; London, Bloomsbury Publishing:
Ljung, M. Swearing: a cross-cultural linguistic study; 2011; New York, Palgrave Macmillan:
Lyons D (2021) How many people speak English, and where is it spoken? Retrieved from https://www.babbel.com/en/magazine/how-many-people-speak-english-and-where-is-it-spoken
Malenova, ED. Translating subtitles–translating cultures. J Siberian Federal Univ Humanit Soc Sci; 2015; 12, pp. 2891-2900. [DOI: https://dx.doi.org/10.17516/1997-1370-2015-8-12-2891-2900]
Manchón, PG. A corpus-based analysis of swearword translation in DVD subtitles and internet fansubs; 2013; Madrid, Spain, (MA Thesis), Universidad Complutense:
Matkivska, N. Audiovisual translation: conception, types, characters’ speech and translation strategies applied. Kalbų studijos; 2014; 25, pp. 38-44. [DOI: https://dx.doi.org/10.5755/j01.sal.0.25.8516]
McEnery, A; Xiao, Z. Swearing in modern British English: the case of fuck in the BNC. Lang Lit; 2004; 13,
Montagu, A. The anatomy of swearing; 2001; Pennsylvania, University of Pennsylvania press:
Moore, RL. On swearwords and slang. American speech; 2012; 87,
Nodoushan, MAS. On the functions of swearing in Persian. J Lang Aggress Conflict; 2016; 4,
O’Hagan, M. Impact of DVD on translation: language options as an essential add-on feature. Convergence; 2007; 13,
O’Driscoll, J. Offensive language: taboo, offence and social control; 2020; United Kingdom, Bloomsbury Publishing: [DOI: https://dx.doi.org/10.5040/9781350169708]
Omar, YZ. The challenges of denotative and connotative meaning for second-language learners. ETC: Rev Gen Semant; 2012; 69,
Pedersen, J. How is culture rendered in subtitles; 2005; Saarbrücken, Paper presented at the MuTra 2005–Challenges of Multidimensional Translation:
Pinker, S. The stuff of thought; 2007; London, England, Penguin Books:
Pujol, D. The translation and dubbing of ‘fuck’into Catalan: The case of From Dusk till Dawn. J Specialised Transl; 2006; 6, pp. 121-133.
Rabab’ah, G; Alali, N. Impoliteness in reader comments on the Al-Jazeera channel news website. J Politeness Res; 2020; 16,
Scott, M. WordSmith tools version 6; 2012; Stroud, Lexical Analysis Software:
Sedighi, A; Najian, TS. On audiovisual translation: The effect of norms of dubbing taboos into Persian movies after the Islamic revolution in Iran. J Lang Transl; 2012; 3,
Simanjuntak, NVN; Basari, A. Subtitling strategies in Real Steel movie. LITE: Jurnal Bahasa, Sastra, dan Budaya; 2016; 12,
Singleton, D. Unspeakable words: the taboo fringe of the lexicon. Adv Discourse Anal; 2009; 130, 146. [DOI: https://dx.doi.org/10.7591/9781501722035-008]
Song, Y; Lin, Q; Kwon, KH; Choy, CH; Xu, R. Contagion of offensive speech online: An interactional analysis of political swearing. Comput Hum Behav; 2022; 127, 107046. [DOI: https://dx.doi.org/10.1016/j.chb.2021.107046]
Stapleton K (2010) Swearing. In: Locher MA, Graham Sage L (eds.) Interpersonal pragmatics. vol. 6. Walter de Gruyter, Germany, p. 289
Stapleton, K; Fägersten, KB; Stephens, R; Loveday, C. The power of swearing: What we know and what we don’t. Lingua; 2022; 277, 103406. [DOI: https://dx.doi.org/10.1016/j.lingua.2022.103406]
Suleiman, SM. Jordanian Arabic between diglossia and bilingualism; 1985; Amsterdam, John Benjamins Publishing Company: [DOI: https://dx.doi.org/10.1075/pb.vi.8]
Vingerhoets, AJ; Bylsma, LM; De Vlam, C. Swearing: a biopsychosocial perspective. Psihologijske teme; 2013; 22,
Yule, G. The study of language; 2020; Cambridge, Cambridge university press:
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Abstract
This study adopts a corpus-assisted approach to explore the translation strategies that Netflix subtitlers opted for in rendering 1564 English swear words into Arabic. It uses a 699,229-word English-Arabic parallel corpus consisting of the English transcriptions of forty English movies, drama, action, science fiction (sci-fi), and biography and their Arabic subtitles. Using the wordlist tool in SketchEngine, the researchers identified some frequent swear words, namely fuck, shit, damn, ass, bitch, bastard, asshole, dick, cunt, and pussy. Moreover, using the parallel concordance tool in SketchEngine revealed that three translation strategies were observed in the corpus, namely, omission, softening, and swear-to-non-swear. The omission strategy accounted for the lion’s share in the investigated data, with 66% for drama, 61% for action, 52% for biography, and 40% for sci-fi. On the other hand, the swear-to-non-swear strategy was the least adopted one, accounting for 21% in sci-fi, 16% in biography, 14% in drama, and 11% in action. In addition, the softening strategy got the second-highest frequency across the different movie genres, with 39% for sci-fi, 32% for biography, 28% for action, and 20% for drama. Since swear words have connotative functions, omitting or euphemizing them could cause a slight change in the representation of meaning and characters. The study recommends more corpus-assisted studies on different AVT modes, including dubbing, voiceover, and free commentaries.
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Details
; Al-Adwan, Amer 3
1 Kent State University, Kent, USA (GRID:grid.258518.3) (ISNI:0000 0001 0656 9343)
2 Applied Science Private University, Amman, Jordan (GRID:grid.411423.1) (ISNI:0000 0004 0622 534X); Middle East University, MEU Research Unit, Amman, Jordan (GRID:grid.449114.d) (ISNI:0000 0004 0457 5303)
3 Hamad Bin Khalifa University, Ar-Rayyan, Qatar (GRID:grid.452146.0) (ISNI:0000 0004 1789 3191)