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
Abstract
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?
Methods
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.
Recruitment
Data
were collected through a subforum (subreddit) post devoted
to survey distribution on Reddit (Reddit.com). 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.
Questionnaire
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).
Demographics
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.
Results
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).
Discussion
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.
References
Ali, S. O., & Peynircioglu, Z. F. (2006). Songs and emotions: Are lyrics
and melodies equal partners. Psychology of Music, 34(4), 511-534. doi: 10.1177/0305735606067168
An, H. S., Chung, C., & Muk, A.
(2020). The effects of social media WOM and fan pages on young Americans’
intentions to purchase foreign pop. International Journal of Business
and Applied Sciences, 9(3), 1–16. Retrieved from https://ijbas.com/wp-content/uploads/2021/01/An-Chung-Muk-2020-93.pdf
Bad Bunny: Chart
history. (n.d.). Billboard. https://www.billboard.com/artist/bad-bunny/
Ballard, J. (2018,
September 20). Many Americans think Latin culture has had a positive
influence on American music. YouGovAmerica. https://today.yougov.com/topics/entertainment/articles-reports/2018/09/20/americans-music-tv-spanish-hispanic
Barker, V., Giles,
H., Noels, K., Duck, J., Hecht, M., & Clement, R. (2001). The English-only Movement:
A communication analysis of changing perceptions of language vitality. Journal
of Communication, 51(1), 3-37. doi:10.1111/j.1460-2466.2001.tb02870.x
Belcher, J. D.,
& Haridakis, P. (2013). The role of background
characteristics, music-listening motives, and music selection on music discussion. Communication Quarterly, 61(4),
375–396. https://doi.org/10.1080/01463373.2013.776986
Bello, P., &
Garcia, D. (2021). Cultural Divergence in popular music: The increasing
diversity of music consumption on Spotify across countries. Humanities and
Social Sciences Communications, 8, 1–26.
https://doi.org/10.1057/s41599-021-00855-1
Blokur,
S. (2021, August 26). With over 60% of YouTube’s top songs in a non-English
language, is music written in English losing its dominance. Medium. https://medium.com/blokur/is-music-written-in-english-losing-its-dominance-54bf93a8fb5f
Brittin,
R. (2014). Young listeners’ music style preferences: Patterns related to
Cultural Identification and language use. Journal of Research in Music
Education, 61(4), 415-430. https://doi.org/10.1177/0022429413509108
Brown, S. C.,
& Krause, A. E. (2020). Freedom of choice: Examining music listening as a
function of favorite music format. Psychomusicology:
Music, Mind and Brain, 30(2), 88-102. https://doi.org/10.1037/pmu0000254
Business of Apps
(2023). Spotify revenue and usage statistics [Data file]. Retrieved from
https://www.businessofapps.com/data/spotify-statistics/#:~:text=Source%3A%20Company%20data-,Spotify%20subscribers,100%20million%20in%20Q1%202019
Byrne, B. P., & Gopaldas, A. (2020, April 3). Radio, why won’t you play
BTS? Now This News. https://nowthisnews.com/pop/radio-why-wont-you-play-bts
Cain, J. A., (2011). The
album-buying niche: The future of recorded music on
traditional media. Southwestern Mass Communication Journal, 27(1),
15-26.
Chin, T., & Rickard, N. S.
(2012). The music use (MUSE) questionnaire: An instrument to measure engagement
in music. Music Perception: An Interdisciplinary Journal, 29(4),
429-446. https://doi.org/10.1525/mp.2012.29.4.429
Cleofas, J. V., Albao, B.T., & Dayrit, J.C.S.
(2022). Emerging adulthood uses and gratifications of social media during the
COVID-19 pandemic: A mixed methods study among Filipino college students. Emerging
Adulthood, (10)6, 1602-1616. https://doi.org/ 10.1177/21676968221128621
Cotter, K. N., Prince, A. N.,
Christensen, A. P., & Silvia, P. J. (2019). Feeling like crying when
listening to music: Exploring musical and contextual features. Empirical
Studies of the Arts, 37(2), 119-137. https://doi.org/10.1177/0276237418805692
Curry, D. (2023a, February 1). Music
streaming app revenue and usage statistics (2023). Business of Apps. https://www.businessofapps.com/data/music-streaming-market/
De la Rosa Herrera, K., &
Pugliese, R. (2017). The uses and gratifications of music among emerging
adults. International Journal of Arts and Sciences, 10(1), 351-364.
Dietrich, S., & Hernandez, E.
(2022, December 6). Nearly 68 million people spoke a language other than
English at home in 2019. U.S. Census Bureau. https://www.census.gov/library/stories/2022/12/languages-we-speak-in-united-states.html
Diez, B. (2019, December 3). ‘English
Only’: The movement to limit Spanish speaking in U.S.. BBC. https://www.bbc.com/news/world-us-canada-50550742
For the record: The rise of
international music in the U.S. (2021, August 12). Genius. https://genius.com/a/for-the-record-the-rise-of-international-music-in-the-u-s
Goltz, F., & Sadakata,
M. (2021). Do you listen to music while studying? A portrait of how people use
music to optimize their cognitive performance. Acta Psychologica,
220, 1-11. performance. Acta Psychologica, 220. https://doi.org/10.1016/j.actpsy.2021.103417
Greasley, A. E., & Lamont,
A. M. (2006). Music preference in adulthood: Why do we like the music we do. Proceedings of the International Conference on Music
Perception and Cognition, 960-966.
Griffin, E., Ledbetter, A., &
Sparks, G. (2019). Uses and gratifications. In A first look at communication
theory (pp. 346–355). McGraw-Hill Education.
Gurgen, E.T. (2016). Social
and emotional function of music listening: Reasons for listening to music. Eurasian
Journal of Educational Research, 16(66), 229-242. http://doi.org/10.14689/ejer.2016.66.13
Gutierrez, J. A. W. (2018). Students
evaluate music theory courses: A Reddit community survey. College Music
Society, 58(2), 1-27. https://doi.org/10.18177/sym.2018.58.sr.11391
Higgins, S. (2021, February
14). Does language matter anymore when it comes to pop music success.
Vogue.
https://www.vogue.com/article/does-language-matter-pop-music-bts-blackpink-maluma-despacito
Hodak, B. (2018, March 6). New
study spotlights Gen Z’s unique music consumption habits. Forbes. https://www.forbes.com/sites/brittanyhodak/2018/03/06/new-study-spotlights-gen-zs-unique-music-consumption-habits/?sh=48e5d98b42d0
IFPI. (2022a). Engaging with
music 2022. https://www.ifpi.org/wp-content/uploads/2022/11/Engaging-with-Music-2022_full-report-1.pdf
IFPI. (2022b). Global music
report. https://www.ifpi.org/wp-content/uploads/2022/04/IFPI_Global_Music_Report_2022-State_of_the_Industry.pdf
Ingham, T. (2022, April 12). Latin
music is on course to generate over $1 billion in the U.S. in 2022. Music
Business Worldwide. https://www.musicbusinessworldwide.com/latin-music-is-on-course-to-generate-over-1-billion-in-the-us-in-2022/
Kim, J., &
Kwon, S. H. (2022). K-Pop’s global success and its innovative production
system. Sustainability, 14, 2-17. https://doi.org/10.3390/ su141711101
Kinnally,
W., & Bolduc, H. (2020). Integrating the theory of planned behavior and
uses and gratifications to understand music streaming intentions and behavior. Atlantic
Journal of Communications, 28(3), 165-179. https://doi.org/10.1080/15456870.2020.1718676
Kircaburun,
K., Alhabash, S., Tosuntas,
S.B., & Griffiths, M.D. (2020). Uses and gratifications of problematic social
media use among university students: A simultaneous examination of the big five
of personality traits, social media platforms, and social media use motives. International
Journal of Mental Health and Addiction, 18, 525-547. https://doi.org/10.1007/s11469-018-9940-6
Krause, A. E.,
& Brown, S. C. (2021). A uses and gratifications approach to considering
the music formats that people use most often. Psychology of Music,
49(3), 547-566. doi: 10.1177/0305735619880608
Kuntsche,
E., Le Mevel, L., & Berson,
I. (2015). Development of the four-dimensional Motives for Listening to Music
Questionnaire (MLMQ) and associations with health and social issues among
adolescents. Psychology of Music, 44(2), 219-233. https://doi.org/10.1177/0305735614562635
Lonsdale, A. J.,
& North, A. C. (2011). Why do we listen to music? A uses and gratifications
analysis. British Journal of Psychology, 102, 101-134. doi:10.1348/000712610X506831
Lozic,
J. (2019). Digitalization creates a new paradigm of the global music industry:
The traditional music industry is under pressure of the
streaming platforms. Proceedings from International Scientific Conference on
Economic and Social Development, 179-190.
Ma, Y., Baker, D.
J., Vukovics, K. M., Davis, C. J., & Elliott, E.
M. (2023). Lyrics and melodies: Do both affect emotions equally? A replication
and extension of Ali and Peynircioglu (2006). Musicae
Scientiae, 1-13. https://doi.org/10.1177/10298649221149109
McCain, A. (2022,
December 19). 30 harmonious music industry statistics [2023]: Facts, trends,
and sales. Zippia. https://www.zippia.com/advice/music-industry-statistics/#:~:text=The%20music%20industry%20is%20worth%20%2425.9%20billion.&text=In%202021%2C%20the%20U.S.'s,subscribers%20to%20music%20streaming%20services
Morris, J. W.
(2020). Music platforms and the optimization of culture. Social Media and Society,
1-10. https://doi.org/10.1177/2056305120940
Music streaming
statistics in 2023 (U.S. and global data). (2022, December 28). Musical
Pursuits. https://musicalpursuits.com/music-streaming/
Mykhailyuk,
O. Y., & Pohlod, H. Y. (2015). The languages we
speak affect our perceptions of the world. Journal of JPNU, 2(2), 36-41.
https://doi.org/10.15330/jpnu.2.2.36-41
Pelletier, M. J., Krallman, A., Adams, F. G., & Hancock, T. (2020). One
size doesn’t fit all: A uses and gratifications analysis of social media
platforms. Journal of Research in Interactive Marketing, 14(2), 269-284.
https://doi.org/10.1108/JRIM-10-2019-0159
Peretz,
I., & Hebert, S. (2000). Toward a biological account of music experience. Brain
and Cognition, 42(1), 131-134.
Reddit. (n.d.). Dive
into anything. https://www.redditinc.com/95
RIAA. (2021). 2021
U.S. consumer music profile. https://www.riaa.com/reports/2021-u-s-consumer-music-profile-musicwatch-inc.pdf
RIAA. (2022). 2022
Mid-year music industry revenue report. https://www.riaa.com/reports/2022-mid-year-music-industry-revenue-report-riaa.pdf
Rivera-Rideau, P.,
& Torres-Leschnik, J. (2019). The colors and
flavors of my Puerto Rico: Mapping “despacito”’s
crossovers. Journal of Popular Music Studies, 31(1), 87-108. https://doi.org/10.1525/jpms.2019.311009
Schafer, T.
(2016). The goals and effects of music listening and their relationship to the
strength of music preference. PloS one,
11(3), 1-15. doi:10.1371/journal.pone.0151634
Schafer, K., & Eerola, T. (2018). How listening to music and engagement
with other media provide a sense of belonging: An
exploratory study of social surrogacy. Psychology of Music, 48(2),
232-251. https://doi.org/10.1177/0305735618795036
Schafer, T., & Sedlmeier, P. (2010). What makes us like music:
Determinants of music preference. Psychology of Aesthetics, Creativity, and
the Arts, 4(4), 223-234. https://doi.org/10.1037/a0018374
Shatz,
I. (2015). The negative impact of goal-oriented instructions. Educational
Studies, 41(5), 476-480. http://doi.org/10.1080/03055698.2015.1043982
Shatz,
I. (2017). Fast, free, and targeted: Reddit as a source for recruiting
participants online. Reports and Communications, 35(4), 537-549. https://doi.org/10.1177/0894439316650163
Simon, J. P. (2019). New players in the music industry:
lifeboats or killer whales? The role of streaming platforms. Digital Policy,
Regulation and Governance, 21(6), 525-549.
Statista. (2022a). Apple music
users in the U.S. 2018, by age [Data file]. Retrieved from
https://www.statista.com/statistics/822920/apple-music-user-age/
Statista. (2022b). Coronavirus
impact on global music revenue growth 2019-2020 [Data file]. Retrieved from
https://www.statista.com/statistics/1172357/coronavirus-music-revenue-growth-worldwide/
Statista. (2022c). Digital
music: United States [Data file]. Retrieved from https://www.statista.com/outlook/dmo/digital-media/digital-music/united-states
Statista. (2022d). Music
consumption in the U.S. 2021 [Data file]. Retrieved from
https://www.statista.com/statistics/502908/music-consumption-genre-format-usa/
Statista. (2022e). Music
streaming: United States [Data file]. Retrieved from
https://www.statista.com/outlook/dmo/digital-media/digital-music/music-streaming/united-states#revenue
Statista.
(2022f). Reddit app user ratio in the U.S. 2021, by age group [Data
file]. Retrieved from https://www.statista.com/statistics/1125159/reddit-us-app-users-age/
Statista. (2022g). Spotify:
Artists with the most monthly listeners worldwide 2022 [Data file].
Retrieved from
https://www.statista.com/statistics/1032826/spotify-artists-monthly-listeners-worldwide/
Statista. (2022h). Spotify:
Statistics and facts [Data file]. Retrieved from
https://www.statista.com/topics/2075/spotify/#topicOverview
Statista. (2022i). Streamed
music consumption in the U.S. 2021 [Data file]. Retrieved from
https://www.statista.com/statistics/475667/streamed-music-consumption-genre-usa/
Statista. (2022j). U.S. music
industry: Revenue distribution 2017-2021 [Data file]. Retrieved from
https://www.statista.com/statistics/186304/revenue-distribution-in-the-us-music-industry/
Thompson, W. F., Geeves, A. M., Olsen, K. N. (2019). Who enjoys listening to
violent music and why. Psychology of Popular Media Culture, 8(3),
218-232. http://dx.doi.org/10.1037/ppm0000184
Todd, L. (2018,
November 21). K-pop and Latin: Why the time is now for foreign language hits.
BBC. https://www.bbc.com/news/entertainment-arts-46032162
Trust, G. (2022,
August 4). 64 Fun facts from the Billboard Hot 100’s first 64 years: From
Ricky Nelson to Lizzo and more. Billboard. https://www.billboard.com/music/chart-beat/hot-100-64-years-fun-facts-ricky-nelson-lizzo-1235122282/
Tse,
L. (2000). Student perceptions of foreign language study: A qualitative
analysis of foreign language autobiographies. The Modern Language Journal,
84(1), 69-84.
Turner, A. (n.d.).
Number of Apple music users and subscribers’ growth in 2023. Bankmycell. https://www.bankmycell.com/blog/number-of-apple-music-users
United States
Census Bureau. (2019). Language use in the United States [Data file].
Retrieved from https://www.census.gov/library/publications/2022/acs/acs-50.html#:~:text=English%20is%20the%20most%20common,U.S.%20population%20speaking%20only%20English.
Vanstone, A. D.,
Wolf, M., Poon, T., & Cuddy, L. L. (2016). Measuring engagement with music:
Development of an informant-report questionnaire. Aging and Mental Health,
20(5), 474-484. https://doi.org/10.1080/13607863.2015.1021750
Vizcaino-Verdu, A., De-Casas-Moreno, P., & Tirocchi,
S. (2023). Online prosumer convergence: Listening, creating, and sharing music
on YouTube and TikTok. Communication and Society, 36(1), 151-166. doi:10.15581/003.36.1.151-166
Volokhin,
S., & Agichtein, E. (2018). Understanding music
listening intents during daily activities with implications for contextual
music recommendation. Proceedings of the Conference on Human Information
Interaction and Retrieval, 313-316. https://doi.org/10.1145/3176349.3176885
Walker, J. L.
(1974). Opinions of university students about language teaching. Foreign Language
Annals, 7(5), 102-105. Retrieved from https://onlinelibrary.wiley.com/doi/pdf/10.1111/j.1944-9720.1974.tb00088.x
What Spotify data
show about the decline of English. (2022, January 29). The Economist. https://www.economist.com/interactive/graphic-detail/2022/01/29/what-spotify-data-show-about-the-decline-of-english
Whittle, C., &
Eaves, M. (2016). College students’ uses and gratifications of online music
streaming for music listening. Journal of Social Sciences Research, 4,
4-20.
Yoo,
H., Kang, S., & Fung, V. (2017). Personality and world music preference of
undergraduate non-music majors in South Korea and the United States. Psychology
of Music, 46(5), 611-625. Doi: 10.1177/0305735617716757
Yoon, K. (2018).
Global imagination of K-pop: Pop music fans’ lived experiences of cultural
hybridity. Popular Music and Society. 41(4), 373-389. https://doi.org/10.1080/03007766.2017.1292819
YouTube. (2023). YouTube
records. [Data file]. Retrieved from https://www.youtube.com/trends/records/