Motivations and Habits of Music Preferences Among Young Audiences


Therese Breithaupt

Department of Humanities, DeSales University

CM-405: Professional Communication Seminar

Dr. Katherine Grasso

May 1, 2023















            This study aimed to explore differences in foreign language music (FLM) listening and native language music (NLM) listening motivations and habits. Participants rated engagement frequency of eight motivations—based on uses and gratifications theory—for their FLM and NLM habits, with monolingual and bilingual participants’ frequencies being compared. Overall findings indicated a wider acceptance of NLM in social situations, suggesting that the language of lyrics does play a role in listening habits. Furthermore, bilingual listeners reported overall higher frequencies of FLM listening, suggesting a greater acceptance of FLM for several motivators in comparison to monolingual listeners. 

Motivations for Language Preference in Music Among Young Adults

Since the Internet’s arrival and the introduction of the smartphone, the digital world has continued to expand. While this digitization has changed how people interact, engage with each other, and gather information via social media applications and platforms, it has also shifted how and why people listen to music (Pelletier et al., 2020). This is a notable shift due to the current size of the music market. In 2021, the global music industry earned $25.9 billion, with the U.S. accounting for $15 billion (McCain, 2022). More people are listening to music than ever before (Brown & Krause, 2020) and digital streaming services are to thank (Bello & Garcia, 2021; McCain, 2022; Schafer, 2016; Simon, 2019; Statista, 2022c).

As digital streaming services (e.g., Spotify, Apple Music, Pandora) and social media platforms (e.g., TikTok, YouTube) continue to dominate the music market, non-English and global music has become easier to discover and as a result, grow in popularity (An et al., 2020). With non-English speaking artists and music on the rise (An et al., 2020; Blokur, 2021; Higgins, 2021; Kim & Kwon, 2022), questions emerge as to why individuals listen to music that is in a language foreign to them. Applying uses and gratifications theory, this study aims to identify the motivators behind audiences who listen to music in a foreign language, as well as the motivators behind audiences who only listen to music in their native language and assess the differences.

Global Music Industry

            The genesis of social media and music streaming platforms shifted how music listeners around the world buy and consume music (Bello & Garcia, 2021; Kinnally & Bolduc, 2020; Lozic, 2019; Morris, 2020; Simon, 2019). Initially built upon physical sales, the music industry transformed with the digitization of media; digital music has led to a greater dissemination of different artists and genres, with audiences having the ability to consume more music than ever before. Additionally, this shift ultimately rescued the industry’s once not so hopeful future. For, at the turn of the century, global recorded music industry revenues took a downward hit and settled at $23.4 billion, $2 billion less than the year before (Simon, 2019). Within the next decade (2000s), global revenue dropped further to $14.9 billion. The industry hit an all-time low for the century at $14.2 billion in 2014. However, the next year, when music streaming platforms began to saturate the market, the global recording industry saw its first significant revenue increase since the 1990s. Global revenues have continued to increase since this spark. Moreover, when the Coronavirus first hit in March 2020, individuals flocked to media for social and entertainment needs, in turn increasing the demand for audio and video entertainment, naturally raising global revenue with it (Cleofas et al., 2022; “Music streaming statistics,” 2022; Statista, 2022b). This demand helped the industry finally surpass the century entrance revenue at $25.9 billion in 2021 (IFPI, 2022b). All seven regions posted revenue growth, with five regions—Middle East and North Africa (35%), Latin America (31.2%), U.S. and Canada (22%), Asia (16.1%), and Europe (14.4%)—experiencing double-digit percentage growth. Of these leading markets, 24% of revenue is attributed to music streaming services/platforms, 19% is video streaming (i.e., YouTube), 17% radio, and 10% purchased digital or physical music (IFPI, 2022a). With the rise of streaming platforms, people are listening to music more than any other point in history, and consequently, industry revenues are growing (Brown & Krause, 2020).

U.S. Music Industry

Making up 60% of the international music industry revenue (McCain, 2022), the U.S. is undeniably a music producing powerhouse. Out of all other national markets, the U.S. showed a 22% increase in revenue growth as the world’s largest market (IFPI, 2022b). Much of this progress is due to music streaming applications and platforms’ continuous popularity. For in 2022, music streaming reached $5.46 billion of revenue in the U.S. alone (Statista, 2022e), exceeding 92 million paid streaming subscribers (Statista, 2022i). This mass, unsurprisingly, drew up almost half of all music streaming app revenue worldwide (Curry, 2023a). Likewise, of the U.S. industry revenue, streaming (paid and ad-supported) accounted for 83%, a 10% increase from 2017 (Statista, 2022j). Just over 82.1 million Americans drove the force of this increase as paid subscribers, stemming from 46.9 million subscribers in 2018 (“Music streaming statistics,” 2022). Recent data suggests that these subscribers spend an average of 75 minutes per day streaming music, with Generation Z leading with almost 100 minutes per day. Certainly, more Americans are invested in the music market more than ever before, and streaming undoubtedly has led such intrigue.

Additionally, music charts such as the Billboard Hot 100 and Top Songs USA Spotify fuel the global music scene (“What Spotify data show,” 2022). Of the language hits on these charts, English songs—almost all produced by American artists—have, for the past five years, comprised between 94-97% if the most streamed tracks. Hence, the number of streams listened to on Spotify and other streaming platforms, is an important indicator of the charting and overall success of an artist (Statista, 2022g). 

Although the U.S. music industry declined at the beginning of the century, nothing prepared it or Americans for its laudable comeback, much if not all accredited to the development and adoption of digital streaming services. The future appears to be even more promising, as 168.3 million streamers of digital music are expected by 2027 (Statista, 2022e).

Digital Streaming

The introduction of iTunes and the iPod in 2001 started the digital age of music, a revolutionary change (Curry, 2023a). While this music novelty helped the global recording music industry revenue rise 4% to $24.4 billion, copyright infringement and digital piracy led to the start of continuous decline the next year (Simon, 2019). However, in the mid-2000s, revenue numbers steadied (Simon, 2019) as music streaming services/platforms (Pandora and Spotify) were launched (Curry, 2023a). In 2010, YouTube became the most popular hub for music video publishing and distribution, and in 2015 Apple launched Apple Music. With these two growing powerhouses, streaming platforms solidified their place in the market (Simon, 2019). 

Undoubtedly, digital music and its platforms have altered how individuals consume music as a media. The fastest and largest growing variable of industry revenue are streaming services (e.g., Spotify, Apple Music, YouTube Music), which now dominate the music market. As of now, U.S. consumers have adopted streaming as their primary means to discover, listen, and share music (Kinnally & Bolduc, 2020), for almost one trillion streams have amassed in the U.S. alone (Statista, 2022d).

In 2021, music streaming accounted for 65% of global industry revenue (McCain, 2022) and in 2022, music streaming reached $5.46 billion of revenue in the U.S. alone (Statista, 2022e). The largest percentage of total subscribers of a music streaming market is Spotify (31%), with Apple Music (15%), Amazon (13%) and YouTube (8%) following behind (McCain, 2019). Similar to this trend, users by application falls from YouTube at two billion, to Spotify (433 million), to Apple (80 million), to Amazon (75 million) (Curry, 2023a).

Much of this growth is due to the services’ ease of accessibility (De la Rosa Herrera & Pugliese, 2017). Further, these digital streaming services continue to offer vast collections of music genres, styles, and language categories, making all forms of music—not just Western mainstream hits—accessible (Bello & Garcia, 2021; Brown & Krause, 2020; Schafer, 2016). For example, Spotify houses over 100 million songs with 60,000 new songs added everyday (Business of Apps, 2022) and Apple Music, while also housing 100 million songs, garners about 20,000 additions everyday (Turner, n.d.). These seemingly unlimited libraries allow users to discover new music through algorithmic/curated recommendations, search abilities, and category playlists (e.g., Latin, R&B, K-pop) (Gurgen, 2016; Volokhin & Agichtein, 2018; Whittle & Eaves, 2016). Listeners can choose whatever music they want to listen to, whenever they want (Schafer, 2016; IFPI, 2022a).

User Demographics

Recent surveys indicate 90% of Millennials and Generation Z use at least one music streaming app and that younger individuals tend to listen to more music than older individuals (An et al., 2020; Schafer, 2016; Volokhin & Agichtein, 2018). Naturally then, data has revealed that the largest user group of music streaming in 2022 was 25-to-34-year-olds (Statista, 2022h), with Generation Z following close behind, making up 49% of paid streaming service subscribers (RIAA, 2021). Platform specifically, among Spotify’s global 489 million unique users, 102 million were North American users (Business of Apps, 2023). Of these users, 29% were between the ages of 25 and 34, with the second highest group comprising of 18- to 24-year-olds at 26% (Business of Apps, 2023). Spotify’s annual users were home to Europe (146 million), North America (102 million), Latin America (103 million), and other countries (137 million). In comparison, Apple Music amassed 88 million users over its availability in 167 countries, 33 million of which the U.S. accounted for (Turner, n.d.). Currently there is no other data on either platform’s user demographics regarding U.S. user ethnicities or spoken languages.

Non-English Music & Global Artist Popularity

There is no doubt that the Western music scene and American pop fuel the global music market. However, with the current rise of music streaming services, it has become easier to discover new music, especially that from other countries, languages, and cultures (An et al., 2020; Kim & Kwon, 2022), as there is “no barrier to consumption” (Todd, 2018). Without these platforms, early global hits such as PSY’s “Gangnam Style” and Luis Fonsi and Daddy Yankee’s “Despacito” would not have amassed YouTube views and likes for several consecutive years (Blokur, 2021). While these songs are of the past and might be considered one-hit wonders, one cannot deny the world’s and specifically, the U.S.’s recent desire, for non-English music (Higgins, 2021; Rivera-Rideau & Torres-Leschnik, 2019). As English is the predominant language spoken in the U.S. (United States Census Bureau, 2019), it is natural that English songs dominate Billboard and Spotify charts. However, several non-native English-speaking artists (individuals whose first language is not English and who primarily sing in their native language) have risen in popularity in the U.S., namely Bad Bunny, BTS, BLACKPINK, Rosalia, and Anitta (“For the Record,” 2021; Higgins, 2021; Ingham, 2022). For example, Bad Bunny, a Puerto-Rican singer, and rapper, was the most streamed artist on Spotify in 2020 with 8.3 billion streams and again in 2021 (“What Spotify data show,” 2022), when Apple Music named him their ‘Artist of the Year’ (Turner, n.d.). He has also recently garnered eight top ten hits on the Billboard Hot 100 between 2018 and 2022 (Trust, 2022; Zelner, n.d.). Furthermore, Bad Bunny and fellow Latin artists, Anitta and Becky G, helped lead the 6.89% Latin music market share of U.S. streaming in 2021 (Ingham, 2022). BTS, a seven-piece boy group from South Korea, has also seen recent success in the U.S. (Higgins, 2021). Currently, BTS holds the record for nine out of the top ten 24-hour music debuts on YouTube with the most views and ranks number two on YouTube’s most subscribed music artist channels (YouTube, 2023). Additionally, in 2020, the group reached 8 billion streams on Spotify, becoming the first Asian act to do so.

These Latin and Korean artists are disrupting the paramountcy of English music. Billboard charts, although heavily relying on radio airplay, have listed BTS five times with top ten hits (Zelner, n.d.) and Bad Bunny with eight top ten hits on the Hot 100 (“Bad Bunny: Chart history,” n.d.). Because most radio streamed music is in English (Todd, 2018), BTS and Bad Bunny’s dominance of these charts is ever more impressive. There is no doubt a growing upward trend in interest of non-English music and artists.

Language Perception and Foreign Music

            In the Western world, English remains king in all aspects: government policy, marketing and advertisement, entertainment media, etc. (Barker et al., 2001, Diez, 2019). In the case of music, it is no different. English-only movements, driven by insecure language majorities threatened by a minority group’s perceived or true increased vitality, continue to hinder non-English forces (Barker et al., 2001). This phenomenon flows into the global music scene, for foreign language music, from the U.S./Western perspective, is often introduced and set in the “World Music” category, a niche market that encompasses all languages outside of English, with which is viewed as distant and exotic (Yoon, 2018). When things become viewed as distant, people tend to avoid such things, labeling them as unknown and thus uncomfortable to engage with. Labeling such as this can lead to negative perceptions of foreign language music, thus deterring people from exploring non-English music and artists. This language apprehension is evident in the limited radio play of non-English artists such as BTS (Byrne & Gopaldas, 2020). Byrne and Gopaldas (2020) noted that the radio industry fears non-English music will discourage audiences from listening, even when such music artists hold massive popularity. Inherent bias towards non-English music make derive from pre-existing negative perceptions. Without inclusion, especially on popular public streaming such as FM radio stations, non-English music will continue to be perceived as distant and obscure (Byrne & Gopaldas, 2020).

While there is research on basic foreign language perception (Mykhailyuk & Pohlod, 2015; Tse, 2000; Walker, 1974), a recent interest in language perception in entertainment and music has increased. For example, from a 2018 survey asking about Americans’ thoughts on Hispanic and Latinx representation in entertainment, one third agreed that there should be greater representation (Ballard, 2018). In regard to Spanish and Latin music, 50% agreed that they enjoyed songs sung in a foreign language. Not surprisingly, however, of all generations included in the study, Millennials supported pushes for more Hispanic and Latinx entertainment representation, specifically music artists, the most. Similarly, Generation Z is likely more open to and said to listen to diverse music because of the immense databases at their fingertips (Hodak, 2018).

With 20% of the U.S. population speaking a language other than English at home (Dietrich & Hernandez, 2022), past negative opinions on foreign language media, from native English speakers, seem to be disappearing. With streaming services and social media providing these younger generations to further embrace their own and others’ diversity, intimidation of foreign languages and negative foreign language perception is fading, and foreign language music listening is helping.

Music Experience

            With the ubiquitous nature of music in this modern age, individuals are frequently exposed to music (Greasely & Lamont, 2006; Volokhin & Agichtein, 2018). When listening to music, whether consciously/unconsciously or intentionally/inadvertently, one is experiencing a multisensory activity (Chin & Rickard, 2012). However, when music is actively sought, individuals’ motivations for listening vary greatly.

            Chin and Rickard (2012), Kuntsche et al. (2016), and Vanstone et al. (2016), concerned with music’s unique experience, developed three unique and reliable questionnaires to gain a better understanding of how prevalent music is in an individual’s life and how often one engages with music. Chin and Rickard (2012) and Vanstone et al. (2016) formed similar questionnaires. Introduced first of the two, Chin and Rickard’s (2012) questionnaire, Music USE (MUSE), assessed the quality and quantity of various music uses and levels of engagement. Vanstone et al.’s (2016) Music Engagement Questionnaire (MusEQ) quantified individuals’ differences in music engagement; however, because this study’s participant population consisted of Alzheimer’s patients and its questions were more health oriented, the questionnaire’s engagement type breadth was limited. While these two studies provided some insight into how and how often people interact with music, neither provided sufficient discussion of why people engage with music. However, considering this lack of concentration on listening motivation, Kuntsche et al. (2016) developed a questionnaire (MLMQ) to determine the common motives for intentional music listening. This study for the MLMQ, Motives for Listening to Music Questionnaire, included 4,524 adolescent participants to confirm its overall validity (Kuntsche et al., 2016). Listening was classified as either having a positive valence, increasing positive feelings/emotions, or a negative valence, decreasing negative feelings/emotions (Kuntsche et al, 2016). Additionally, perceived change from listening was considered internal, one’s own emotional and physical sensations, and/or external, sensations in relation to others (Kuntsche et al., 2016). Most frequently, participants noted that they used music to manage mood and cope with negative feelings (Kuntsche et al., 2016).

Lyrics v. Melody

            While sufficient research has been conducted on how humans perceive and experience music (Chin & Rickard, 2012; Cotter et al., 2019; Goltz & Sadakata, 2021; Peretz & Hebert, 2000; Schafer & Eerola, 2018; Schafer & Sedlmeier, 2010; Simon, 2019; Vanstone et al., 2016; Vizcaino-Verdu et al., 2022), fewer studies have strictly dissected and separated the experience of a song into its lyrics and musical qualities (i.e., melodies, instrumentation, rhythm) (Ali & Peynircioglu, 2006; Ma et al., 2023; Thompson et al., 2019).

Ali and Peynircioglu (2006) conducted four similar experiments on emotional judgments of lyrical and non-lyrical music. Each study consisted of 32-36 participants of university age who completed a specific survey based on one of the four experiments to which they had been assigned. Experiment I and II of the research concentrated on lyrics versus melodies and intended emotion of an excerpt. After being given multiple short song excerpts to listen to, participants of both experiments stated lyrics as increasing the emotion conveyed in the song (i.e., sad, or angry). However, it was also found that the melody of an excerpt produced a greater effect on participants’ emotional responses than lyrics did (Ali and Peynircioglu, 2006).

Ma et al. (2023), a replication study, found that overall, participants rated lyrical song excerpts higher than instrumental song excerpts. While no research currently exists on the effects of foreign-language music listening—besides in the educational classroom with foreign language acquisition (Tse, 2000; Walker, 1974)—and its purpose, Ali and Peynircioglu (2006) and Ma et al. (2023) provide some insight into how lyrics, or in this case being able to understand foreign lyrics, affects an individual’s musical preference. Although these two studies elicited incongruent results, their results could support why some individuals actively seek foreign-language and world music, while others exclusively seek music of their native language.

Similarly, Thompson et al. (2019) investigated emotional and lyrical awareness induced by violent music with two participant groups, those who actively consumed heavy metal death music (fans) and those who did not consume violent music at all (non-fans). When questioned about their assessment of the misogynist lyrical content of the given excerpts, participants of the fan group stated their deliberate choice to avoid engaging in critical and conscious thought while listening (Thompson et al., 2019). In contrast, to the nonfan group, these violent themes produced greater alienation to the genre than before (Thompson et al., 2019). The lyrical content was indeed more insignificant to the fan group than to nonfan group, suggesting that both populations experienced music differently, gratifying different needs (Thompson et al., 2019). In a similar fashion, this study can provide a basis for understanding why individuals consume foreign music and others do not. Just as participants in the fan group avoided conscious involvement with the lyrics, so too might individuals who listen to foreign language music avoid conscious involvement with lyrics because of language incomprehension. Thompson et al. (2019) reveals that lyrics are not all that individuals seek when preferring one genre or music form over another.



Uses and Gratifications Theory

In this ever-advancing digital and technological age, individuals make daily choices to consume and frequent various forms of media (Belcher & Haridakis, 2013). These choices are led by a consumers’ personal needs and desires, which are unique to themselves. Elihu Katz’s uses and gratifications theory (UGT) was proposed to address and understand these personal drives behind media usage (Griffin et al., 2019). Rather than focusing on how media influences consumers, Katz emphasized the human experience by focusing on why consumers use different types of media. Although introduced in the late 1950s to examine traditional media (e.g., newspapers, radio, television), UGT continues to remain relevant to the media of today (e.g., smartphones, the Internet, social media). This framework allows for a greater understanding of both motives for selecting modern media and resulting gratifications gained through this media use (Griffin et al., 2019). Five assumptions underly UGT: 1) People use media for their own intentions, 2) Through media choice, people seek to gratify needs, 3) Media competes for people’s attention, 4) Media affects different people differently, and 5) People are accurately self-aware of their motives behind personal media use (Griffin et al., 2019; Lonsdale & North, 2011).

UGT Application

Since the advent of UGT research, researchers have fashioned many typologies that provide explanations for why individuals intently expose themselves to different media (Griffin et al., 2019). A typology is a classification system that aims to sort large groups of specific data into more broad, manageable categories. A major comprehensive typology of media uses and gratifications was introduced by Alan Rubin in 1981. Consisting of eight motivations, Rubin’s typology accounted for the major reasons why people watch television. The eight categories consisted of passing time/habitual, companionship, escape (from reality), enjoyment, social interaction, relaxation, information, and excitement. It is important to note that these eight motivations may not be mutually exclusive for every individual, for some might solely watch TV for information needs, while others might watch TV for both entertainment and enjoyment  (Griffin et al., 2019). This factor of Rubin’s proposal reinforces the fourth assumption of UGT—the same medium (e.g., TV) and its messages do not affect everyone in the same way.

Several studies that examined users’ motives for social media use have applied UGT and Rubin’s typology to their research (Cleofas et al., 2022; Kircaburun et al., 2018; Pelletier et al., 2020). These studies each found similar motivations for engaging with social media: information/news, entertainment, diversion/convenience (Kircaburun et al., 2018; Pelletier et al., 2020), personal/self-identification, self-autonomy (Cleofas et al., 2022), and social interaction (Cleofas et al., 2022; Kircaburun et al., 2018; Pelletier et al., 2020). Similarly, analyzing specific audio formats or music streaming services, two studies noted autonomy, song/artist discovery, and personal identity as common motives for format and platform preference (Brown & Krause, 2020; Krause & Brown, 2021).

Regarding motivations specifically for music listening and choice through the lens of UGT, there are a handful of studies (Belcher & Haridakis, 2013; Brittin, 2014; Lonsdale & North, 2011; Whittle & Eaves, 2016); however, due to the increased popularity of the music industry, more recent studies have taken music streaming and social media influence on the industry and gratification of consumers into account (Cain, 2011; De la Rosa Herrera & Pugliese, 2017; Kinnally & Bolduc, 2020). De la Rosa Herrera and Pugliese (2017) directly dealt with the needs that individuals seek to satisfy through music and specific music genres, while Kinnally and Bolduc (2020) focused on motives for using music streaming services. Both studies concentrated on young populations and their specific uses and gratifications, as this age demographic is the biggest consumer of social media and digital music. De la Rosa Herrera and Pugliese (2017) found identity and behavioral motives to have significant and positive relationships with six popular genres, and knowledge and information motives to have positively significant relationships with seven genres. On the other hand, Kinnally and Bolduc (2020) found entertainment/mood, discovery, social interaction, and pass time as statistically significant motivations for using digital music streaming services.

While these studies do provide some insight into music distribution, there are little (An et al., 2020) to no studies that thoroughly investigate music consumption, more specifically, motivations for listening to music that is outside of one’s language and consequently, immediate understanding.

Following UGT’s assertion that individuals reach for and entertain certain media, this study aims to distinguish both the differences and similarities between why certain individuals engage in foreign music listening and why others do not.

Research Questions

As previously mentioned, while past research has looked at the motivations behind music listening and preferences using UGT, much of the information and data has grown obsolete as the music market continues to change and progress. Furthermore, as the industry evolves, so too do audiences’ preferences, likes, and needs, as seen with recent hits of non-English songs. To date, no studies have explored the influence of language on music selection and music listening habits, or in other words, the motivations behind this growing phenomenon. To begin to understand these trends, this study will propose two research questions:

RQ 1: Does motivation differ when people listen to foreign language music or native language music?

RQ 2: Do bilingual listeners report different motivations for music listening than monolingual listeners?


Participant Characteristics

Data were collected from both undergraduate students attending a small, private, Catholic university in the mid-Atlantic region and participants from four Reddit posts. The final sample of participants consisted of 73 adults between the ages of 18–35. This set age range was organized to include both the Millennial and Generation Z populations. The majority of participants were between the ages of 18 and 24. While data were originally collected from 121 respondents, 48 participants that were either over the age of 35 or that reported less than an hour of daily music listening, were disqualified. Additionally, because only two participants indicated exclusively listening to NLM, their data was discarded. The majority of the participants were female (54.79%) and identified as white (64.38%). The remaining participants identified as Asian (17.8%), Mixed/Two or more races (13.69%), and Black (4.1%), with 17.8% identifying as Latino or Hispanic.

Of the final sample, 37 (50.68%) were monolingual—only fluent in English—while 36 (49.31%) were bilingual/polyglots—noted languages included Arabic, Hindi, Vietnamese, Spanish, Portuguese, Korean, French, Italian, Chinese, Japanese, Ukrainian, German, Scottish, Gaelic, and Greek. While all participants stated listening to FLM, 68.49% indicated they “definitely” listened to FLM and 31.5% indicated they “sometimes” listened to FLM. Of the FLM listened to, 28+ languages (Arabic, Hindi, Vietnamese, Greek, Czech, Urdu, Malay, Portuguese, Korean, French, Spanish, Chinese, Japanese, Italian, Polish, German, Russian, Turkish, Taiwanese, Pasifika languages, Khmer, Afrikaans, Punjabi, Finnish, Romanian, Mongolian, Swedish, etc.) were represented.


Data were collected through a subforum (subreddit) post devoted to survey distribution on Reddit ( Reddit is a social news website centered around discussion forums where users are allowed to share content and rank posts (Reddit, n.d.). While few research studies have used Reddit to gather survey data (Gutierrez, 2018; Shatz, 2015), this free platform allows for quick participant recruitment of large samples. Specific subreddits related to or on the topic of music and foreign language music listening (i.e., music, K-pop, J-pop) were targeted (Gutierrez, 2018; Shatz, 2017). This allows for a greater chance of recruiting individuals of the target population who qualify based on the set eligibility requirements. Additionally, an analysis of the website’s user demographics indicate that the great majority of users are below the age of 35 (Statista, 2022f), which once more allows for a greater sample size of the target population. No incentive or compensation was provided for completion of the questionnaire.

The link displayed on multiple Reddit forums (‘Let’s Talk Music’, ‘K-pop Thoughts’, ‘J-pop’, ‘Sample Size’) directed participants to a survey created with Qualtrics. An introduction to the questionnaire was presented and informed participants of the research goals, which stated, “to learn more about native language versus foreign language music preference, motivations, and habits.” It also explained the eligibility requirements (i.e., be a music listener between the ages of 18 and 35), the expected duration of the survey (i.e., approximately 5-10 min), and the low associated risks. They were then informed that their results would be strictly confidential and that they were able to exit the survey at any time. Their continuation of the survey indicated their consent. Lastly, if respondents had any questions, the main researcher’s email was provided.


Music Listening Platforms

Similar to both Kinnally and Bolduc (2020) and Krause and Brown (2021), participants were asked about their preferred platform for music listening (Response options: streaming apps (Spotify, Apple Music, Amazon, etc.), online streaming (Youtube), radio, CDs/vinyls, digital purchasing apps (iTunes, Google Play), or not listed). A follow-up question asked if they paid an annual or monthly fee for their preferred platform, so as to measure their overall engagement and investment in the specific music medium. Individuals were then asked about their top motivation for their indicated platform (Response options: low cost/fee, easy to use, new song/music discovery, format/interface, recommended playlists, amount of songs available or other).

Foreign Music Listening (FLM)

            Participants were initially asked whether or not they intentionally sought out foreign language music. If an individual responded “sometimes” or “definitely yes,” they continued answering questions related to foreign music listening; however, if they responded, “ definitely not,” they were directed to the NLM section. This section first asked, “On an average day, how many minutes/hours do you spend listening to foreign language music?” Answers ranged from “I do not listen to foreign language music” to “7+ hours.” Using related measures by Chin and Rickard (2012), respondents then assessed how often they engaged in certain activities while listening to music.  Numerous activities were listed, allowing them to check all that applied (walking, dancing, driving, social events, concerts, studying/doing homework, resting/relaxing, getting dressed/ready, cleaning, working, cooking, exercising, showering, eating, and not listed). Participants then ranked these activities based on how often they participated in them when listening to foreign music (never, rarely, occasionally, frequently, or all the time). Furthermore, to understand more about these participants’ listening habits and characteristics, they were asked when and how they were first introduced to foreign music. To determine when introduced to FLM, respondents were able to choose from “within the past two months” to “have been listening since childhood.” Regarding how they were introduced to FLM, nine options were provided to select from (family, friends, social media (Instagram, Twitter, TikTok), music app recommendation, online video platforms (YouTube), foreign language class, movies/TV, radio, or other). Additionally, the language/s of the FLM they listened to was also asked.

Native and Fluent Language Music Listening (NLM)

            Questions about native language music listening motivations and activities were the same as in the FLM section of the questionnaire. Respondents were directed to this section either if they indicated to have “definitely not” listened to FLM or after completing the FLM section questions. In contrast to the FLM section, however, there were no questions regarding NLM introduction.

Music Listening Motivations

            Similar to Lonsdale and North (2011), respondents were asked why they listen to music. One section asked participants about foreign music listening motivations if they had previously indicated they listened to foreign music, and one section asked participants about native/fluent music listening motivations. A slightly expanded version of Lonsdale and North’s (2011) choices were included, with respondents given the opportunity to check all that applied (for entertainment/fun, to relax, to manage/control moods, for distraction, for motivation, for concentration, for social interaction, for self-expression, and/or not listed). Participants were then asked to rank based on how frequently they listened to music based on these motivations (Response choices: never, rarely, occasionally, frequently, or all the time).


            Demographic questions determined age, race, gender, and language fluency (i.e., monolingual, or bilingual) of all participants at the conclusion of the survey.

Data Analysis

RQ1 was tested with a paired t-test to compare mean rankings of the eight FLM and NLM motivations. A paired test was used, as participants’ answers  for both FLM and NLM section questions hailed from the same individuals. RQ2 was answered through an independent t-test which compared mean rankings between monolingual and bilingual participants’ FLM and NLM motivations. To determine the difference/s between the two groups, an independent t-test was used. While initial research strived to determine group motivation differences between exclusive NLM listeners and FLM listeners but could not be addressed due to inadequate NLM group percentage, a subsidiary analysis was performed. This subsidiary analysis compared FLM and NLM activity frequency through a paired t-test.


            For RQ1, to answer if motivation differs when people listen to foreign language music versus native language music, a paired t-test revealed statistically significant differences for three motivations: mood management/control (p = 0.019), distraction (p = 0.023), and social interaction (p = 0.001). On a Likert scale of 1 (never) to 5 (all the time), participants reported higher frequency for all three NLM motivations, mood management/control (M=3.53, SD=1.31), distraction (M=3.52, SD=1.22), and social interaction (M=2.93, SD=1.39).

For RQ2, to determine if bilingual listeners report different motivations for music listening than monolingual listeners, an independent t-test revealed six overall statistically significant differences across both FLM motivations (entertainment/fun (p = 0.045), relaxation  (p = 0.020), motivation (p = 0.041), concentration (p = 0.003), and social interaction (p = 0.001)) and NLM motivations (social interaction: p = 0.024). For FLM, bilingual participants reported a higher frequency for entertainment/fun (M=3.52, SD=1.22), relaxation (M=3.52, SD=1.22), motivation (M=3.52, SD=1.22), concentration (M=3.52, SD=1.22), and social interaction (M=3.52, SD=1.22). Contrastingly, for NLM, monolingual participants reported a higher frequency for social interaction (M=3.30, SD=1.36).

As for the subsidiary analysis, which used an independent t-test to compare monolingual and bilingual participants’ frequency ratings of FLM and NLM activities, six activities out of fourteen listed, were found to be statistically significant differences. All significant differences were detected in the FLM activities. These included social events (p = 0.002), studying/doing homework (p = 0.006), resting/relaxing (p = 0.013), getting ready/dressed (p = 0.0003), cooking (p = 0.0004), and eating (p = 0.022). Bilingual participants reported a higher frequency than monolingual participants for all six activities: social events (M=2.97, SD=1.25), studying/doing homework (M=3.41, SD=1.20), resting/relaxing (M=3.66, SD=1.33), getting ready/dressed (M=3.36, SD=1.26), cooking (M=3.30, SD=1.26), and eating (M=2.63, SD=1.45).


            The purpose of this study was to determine differences between foreign language music listening and native language music listening motivations. As the first of its kind, this study examined foreign language music motivations against native/fluent language music motivations in audiences of both monolingual and bilingual speakers. While previous research has explored motivations behind media use (Chin & Rickard, 2012; Cleofas et al., 2022; Griffin et al., 2019; Kircaburun et al., 2018; Kuntsche et al., 2016; Pelletier et al., 2020), and some focusing on music listening motivations through UGT (Belcher & Haridakis, 2013; Brittin, 2014; Lonsdale & North, 2011; Whittle & Eaves, 2016), no known studies have explored the differences in motivation between FLM and NLM audiences.

            Of the sample, the majority frequently consumed both FLM and NLM. Overall, participants more frequently looked to mood control, distraction, and social interaction for their NLM listening. These results are congruent with Kinnally and Bolduc’s (2020) study which found distraction and social interaction as statistically significant motivators for music streaming. This study’s results may suggest that lyrics play stronger roles in different listening motivations. For instance, one might look to NLM songs to feel a certain emotion, as the lyrics may be more effective at mood management when completely understood. Moreover, the social interaction motivator may suggest that individuals are more comfortable listening to NLM among peers—as is reinforced by mainstream media outlets—and FLM when alone. Additionally, considering FLM and NLM motivation differences between monolingual and bilingual participants, bilingual participants more frequently used FLM for entertainment, relaxation, motivation, concentration, and social interaction, while monolingual participants more frequently used NLM for social interactions. These findings suggest that bilingual participants, compared to their monolingual counterparts, may be more open to FLM listening. Perhaps this attribute stems from bilingual individuals’ multi-language background. Knowing and understanding multiple languages could indicate a greater acceptance of FLM usage and new FLM acceptance. This finding complements monolingual participants’ tendency to more frequently flock to NLM for social interactions. Monolingual listeners, with a limited language background, are perhaps more comfortable listening to, in the case of this study, English music around peers than foreign music. These findings suggest a greater need for language diversification in the media.

Limitations and Implications

            As with any research, there are limitations to this study. Most notably, there was an unequal size of subgrouping, for an overwhelming majority of respondents indicated listening to FLM, while a handful indicated exclusively listening to NLM. This unequal subgrouping was due both to the non-random sample and a survey flow mistake. The abundance of FLM listener respondents, in part, is due to the survey being posted on music centric forums, especially foreign music listening groups (i.e., K-pop, J-pop, etc.). This perhaps drew a larger number of FLM listeners than if posted solely on general music forums. Additionally, early into data collection, the researcher noticed a survey flow mistake for NLM listeners, where these respondents, after completing the NLM section were not directed to the concluding demographic questions. As a result, their data was discarded. An equal size of both FLM and NLM groups would have provided sufficient data to answer the initial research question as to why some individuals listen to FLM and why others do not.

            Additionally, as this study was based on Uses and Gratifications, which comes with its own limitations, other limitations must be addressed. One assumption of UGT states individuals as accurately self-aware of their motives for media use. Participants of this study might vary in their ability to accurately determine the motivations behind their FLM and NLM listening habits. Further research must be conducted to determine the validity of such an assumption. Moreover, the eight motivations used in this study might not encompass all needs that music listening may satisfy. For example, a study from Yoo et al. in 2017, noted the potential influence of an individual’s personality on media motivations. Personality characteristics may indicate certain motivators, which could have been a confounding variable to this study, and as such, should be further researched.

            Overall, this study provides a foundation for future research on FLM popularity and corresponding listening motivations. The results of this study indicate a strong presence of FLM listeners among both monolingual and bilingual audiences, revealing, perhaps, a growing percentage of FLM listeners in the U.S., which would provide an explanation for the rise in popularity of non-native English-speaking artists (i.e., BTS, Bad Bunny, etc.). Such data could suggest for a greater display of language diversity in the U.S.’s mainstream media, namely in radio play of foreign music artists—from the U.S. or abroad—and in film and TV. Greater language diversification in the media would promote inclusion of all individuals, advocating for more voices to be heard, instead of remaining English bias.

In conclusion, this study intended to examine why some audiences choose to listen to foreign language music and why others do not. Motivation differences between FLM and NLM listening motivations were assessed. Results from the study showed higher frequencies of NLM listening to control mood, distract, and listen with others, while also revealing bilingual listeners as more accepting of FLM in almost all motivations.









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