YouTube Music Videos Research Articles

Hitting the Right Notes: Exploring the Relationship between YouTube Music Videos and Digital User Engagement

Purpose: This study meticulously explored the complexities of online fan engagement, placing a spotlight on the transformative influence of YouTube content produced by the renowned K-pop group, Aespa, and its subsequent impact on user interactions and the group's prevailing image.
 Design/methodology/approach: Utilizing a robust text mining methodology, a comprehensive analysis was conducted on 11,039 comments extracted from a specific Aespa YouTube video. This analysis involved the extraction of frequently occurring words, the deployment of a semantic network analysis, and the strategic use of the Co-occurrence network analysis, which collectively provided a profound understanding of fan perceptions and sentiments.
 Findings: Central to the findings was the revelation of Aespa's groundbreaking concept, which emerged as a cornerstone in captivating and retaining fan engagement. The data illuminated the depth of fans' interest in Aespa's narrative approach, with many expressing admiration for the group's commitment to delivering high-quality productions.
 Research limitations/implications: Their unique blend of music, narrative, and visual aesthetics resonated deeply with the audience, fostering a sense of loyalty and admiration. However, it's imperative to note that the research's purview was limited, focusing solely on comments from one video. This limitation underscores the potential and need for more expansive datasets in subsequent studies, which could provide a more holistic view of fan engagement across multiple content pieces. Additionally, considering the dynamic nature of the K-pop industry and the rapid shifts in public sentiment, there's an evident need for continuous monitoring and analysis.
 Originality/value: This investigation not only offers a renewed perspective on the role of digital influence within the vibrant world of K-pop but also accentuates the paramount importance of innovative and distinctive content in amplifying user engagement. It serves as a testament to the evolving landscape of digital influence in the entertainment sector, where content, creativity, and audience engagement intersect in profound ways.

A text mining approach to the use of “groove” in everyday language

When speaking about music, the term groove can refer to objective qualities, such as rhythmic patterns, or to subjective experiences, such as the pleasurable urge to move to the music. However, the mere juxtaposition of objective musical causes and subjective psychological effects may be too simplistic to fully capture the multifaceted groove phenomenon. We therefore broaden the perspective of groove research by analyzing how people use the term groove in the everyday language of 970,220 comments on 155 YouTube music videos. The corresponding songs were previously rated on groove, operationalized as a pleasurable urge to move. Results show that groove terms were more likely to be used in comments on songs that received higher groove ratings. Resonating with the definition of groove as a pleasurable urge to move, groove terms were very likely to co-occur with movement terms, and comments mentioning groove expressed more positive sentiments. We also found that groove terms were predominantly used to describe objective musical qualities in comments on funk, soul, and R&B songs, suggesting that the use of groove is related to genre. In general, we demonstrate how text mining can be used to review existing definitions and gain new perspectives on current topics in music science.

Framing gender in Moroccan contemporary pop music videos: A content analysis of gender portrayals

This study provides a qualitative analysis of gender portrayals in Moroccan pop music videos. Taking into account previous studies that examined the powerful influence of media in creating social and cultural impacts, the present study explores the extent to which gender is stereotypically represented on YouTube music videos within the Moroccan context, a topic that has been rarely tackled. Given this, the study employs content analysis to systematically examine gender representations in both the visual and verbal aspects of six Moroccan popular music videos that were first released on YouTube in 2020. Results have shown that most of the selected music videos contribute to the reproduction of gender roles and stereotypes through both the lyrics and the visual representations of gender. It has been also demonstrated that female singers are more likely to implement gendered messages in their music videos than male singers who, in turn, attempt to challenge some of the most common gender stereotypes, by normalizing men crying, nurturing, and expressing their emotions in public.

Analysis categories for YouTube music videos: understanding the production and consumption of game music covers on the internet

The objective of the article is to present a category-based analysis of game music cover videos produced and consumed by fans on YouTube. To deal with data produced in ethnographic field research, we have created four categories of artistic performance that attempt to synthesize the production of game music shared by the interlocutors. In this article, we will explain these categories and demonstrate their functioning as an analysis tool while exploring some issues related to social and musical performance. These categories have shown that game music functions as a catalyst through which other cultural practices flow, bringing with them their potential for sociability, conflict, and prejudice.

Old Conflicts in New Media Assemblages: India’s Cow Vigilantism and YouTube

Abstract Since 2014, when the right-wing Bharatiya Janata Party took power, India has witnessed attacks by cow vigilantes (gaurakshaks), who have beaten up and lynched people – mostly in the Muslim community – accusing them of smuggling cows for slaughter. Although vigilantes claim to protect cows, considered sacred in Hinduism, scholars argue they are ‘shadow armies’ and ‘foot soldiers’ in a politically motivated campaign against minorities and marginalized populations. India has a long tradition of cow-related iconography, songs, and music. However, some of these forms and practices have been used by right-wing groups to further their agendas. The rise in cow vigilantism has been accompanied by a surge in digital media that support and further violence, including music videos. This paper focuses on YouTube music videos to investigate how various sociotechnological components form a complex assemblage that enables the articulation and circulation of a highly polarized majoritarian narrative about cows.

Theorizing vernacular discourse in Sinophone transnational space: on Namewee’s YouTube music videos

ABSTRACT This article expands Ono and Sloop’s conceptualization of vernacular discourse in a transnational social media space; namely, YouTube. This article showcases how the YouTube music videos of Namewee, a Malaysian Sinophone musician, construct various identities through working with other oppressed voices in the Sinophone transnational space. Two of Namewee’s musical works featuring Taiwanese YouTubers are particularly examined to explore the concepts of “linguistic minorities,” “place-basedness,” and “vernacular collaboration.” By analyzing the horizontal relationships among minority groups across national borders, this case study elicits further conceptualization of what “vernacular discourses” entail beyond the American English-speaking context.

Tracking Persons-of-Interest via Unsupervised Representation Adaptation

Multi-face tracking in unconstrained videos is a challenging problem as faces of one person often can appear drastically different in multiple shots due to significant variations in scale, pose, expression, illumination, and make-up. Existing multi-target tracking methods often use low-level features which are not sufficiently discriminative for identifying faces with such large appearance variations. In this paper, we tackle this problem by learning discriminative, video-specific face representations using convolutional neural networks (CNNs). Unlike existing CNN-based approaches which are only trained on large-scale face image datasets offline, we automatically generate a large number of training samples using the contextual constraints for a given video, and further adapt the pre-trained face CNN to the characters in the specific videos using discovered training samples. The embedding feature space is fine-tuned so that the Euclidean distance in the space corresponds to the semantic face similarity. To this end, we devise a symmetric triplet loss function which optimizes the network more effectively than the conventional triplet loss. With the learned discriminative features, we apply an EM clustering algorithm to link tracklets across multiple shots to generate the final trajectories. We extensively evaluate the proposed algorithm on two sets of TV sitcoms and YouTube music videos, analyze the contribution of each component, and demonstrate significant performance improvement over existing techniques.

A multi-agent dynamic system for robust multi-face tracking

The paper presents a new architecture framework in the field of expert and intelligent systems which is based on four paradigms: a novel multi-agent dynamic system architecture (MADS), an extended Belief Desire Intention (EBDI) agent community, autonomy-oriented entities (AOEs), and deep learning concepts. The main impact of the proposed framework is a new approach, or even a new way of thinking, which enables integration of the concepts of deep learning, a conventional approach to solving the domain problem, cognitive agents with mental attitudes, and concepts of nature-inspired computing. All these allow the effective use of the framework in the field of intelligent and expert systems. The significance of the framework lies in its flexibility and adaptability based on the formal logical description of EBDI agents, the definition of the behaviour of AOEs, the use of classical modules for domain problem solving, and modules based on deep-learning concepts. We believe that the example of the adaptation of the proposed architecture framework to robust multi-face tracking illustrates the significance of the proposed framework. In this paper, MADS is adapted to the first two stages of a face de-identification pipeline: robust face detection and multi-face tracking. The proposed architecture of MADS has a two-level hierarchical organization. At the first level there is a manager designed as an Extended Belief Desire Intention (mEBDI) agent. The extension of a manager BDI agent consists of a convolutional neural network-based face detector, a set of autonomous-oriented entities for the elimination of false positive face detections, and a trajectory memory. At the second level, there are many tracking agents (trEBDIs) which consist of a basic BDI agent extended with a face tracker based on position and scale correlation filters, a visual appearance memory, and a trajectory memory. The mEBDI and trEBDI agents are defined by the modal logic and are described at the implementation level. The proposed architecture for a robust multi-face tracking system was tested on a subset of YouTube music videos. The qualitative results, as well as the preliminary quantitative results expressed by the standard testing metrics, demonstrate the effective adaptation of the proposed multi-agent dynamic architecture to a robust multi-face tracking system.

Understanding viral video dynamics through an epidemic modelling approach

Motivated by the hypothesis that the spread of viral videos is analogous to the spread of a disease epidemic, we formulate a novel susceptible–exposed–infected–recovered–susceptible (SEIRS) delay differential equation epidemic model to describe the popularity evolution of viral videos. Our models incorporate time-delay, in order to accurately describe the virtual contact process between individuals and the temporary immunity of individuals to videos after they have grown tired of watching them. We validate our models by fitting model parameters to viewing data from YouTube music videos, in order to demonstrate that the model solutions accurately reproduce real behaviour seen in this data. We use an SEIR model to describe the initial growth and decline of daily views, and an SEIRS model to describe the long term behaviour of the popularity of music videos. We also analyse the decay rates in the daily views of videos, determining whether they follow a power law or exponential distribution. Although we focus on viral videos, the modelling approach may be used to understand dynamics emergent from other areas of science which aim to describe consumer behaviour.

Paul Dirac’s view of the Theory of Elementary Waves

Is science open to a new idea? Thomas Kuhn says paradigm shifts sound like gibberish to scientificleaders, and are rejected for that reason. The Theory of Elementary Waves (TEW) is such an idea:quantum particles follow waves moving in the opposite direction. Time always goes forwards. Wefocus on Paul Dirac’s 1930 book The Principles of Quantum Mechanics, applied to TEW. We keepDirac notation and quantum math but replace the picture of how nature is organized. Waveinterference and probabilistic effects occur prior to particle emission. Wave function collapse occursat emission & there is no further interference. We have launched a successful program of teachingthis form of physics in the format of YouTube music videos of five minutes duration. Some of ourvideos have been watched 40,000 times: within YouTube search for “Jeffrey H Boyd” to watch theseamusing videos including one in which Yoda (from Star Wars) solves what Richard Feynman calledthe “Fundamental Mystery of Quantum Mechanics.”

“Do You Hear the People Sing” “Lift Your Umbrella”?

Around the world, music serves as an important element of mobilisation for social movements. Singing songs is not only a peaceful protest technique but also helps to construct a protest identity locating and relating the social movement to its political and social environment. Most importantly, a social movement is to a significant extent remembered through its music, and this determines its future impact on local (contentious) politics. Against this backdrop, this article seeks to understand Hong Kong’s Umbrella Movement through four YouTube music videos, analysing the lyrics, music, and video imagery in order to carve out core elements and values of the Umbrella Movement. Especially given the importance of Hong Kong’s identity as a “global” city with a cosmopolitan culture and past, the peaceful nature of the movement and the rise of a xenophobic localism in the shape of sarcasm are emphasised.

\u201cF*ck It! Let\u2019s Get to Drinking\u2014Poison our Livers!\u201d: a Thematic Analysis of Alcohol Content in Contemporary YouTube MusicVideos

PurposeThe purpose of the present study is to describe the portrayal of alcohol content in popular YouTube music videos.MethodWe used inductive thematic analysis to explore the lyrics and visual imagery in 49 UK Top 40 songs and music videos previously found to contain alcohol content and watched by many British adolescents aged between 11 and 18 years and to examine if branded content contravened alcohol industry advertising codes of practice.ResultsThe analysis generated three themes. First, alcohol content was associated with sexualised imagery or lyrics and the objectification of women. Second, alcohol was associated with image, lifestyle and sociability. Finally, some videos showed alcohol overtly encouraging excessive drinking and drunkenness, including those containing branding, with no negative consequences to the drinker.ConclusionOur results suggest that YouTube music videos promote positive associations with alcohol use. Further, several alcohol companies adopt marketing strategies in the video medium that are entirely inconsistent with their own or others agreed advertising codes of practice. We conclude that, as a harm reduction measure, policies should change to prevent adolescent exposure to the positive promotion of alcohol and alcohol branding in music videos.

Follow the algorithm: An exploratory investigation of music on YouTube

This article presents an exploratory study of the network of associations among 22,141 YouTube music videos retrieved by ‘following’ the platform’s recommender algorithm, which automatically suggests a list of ‘related videos’ to the user in response to the video currently being viewed. As YouTube’s recommendations are predominantly based on users’ aggregated practices of sequential viewing, this study aims to inductively reconstruct the resulting associations between the musical content in order to investigate their underlying meanings. Network analysis detects 50 clusters of tightly connected videos characterised by a strong internal homogeneity across different axes of similarity. We discuss these findings with reference to the literature on music genres and classification, arguing that the emerging clusters can be considered as ‘crowd-generated music categories’. That is, sets of musical content that derive from the repeated, crowd-based actions of sequential viewing by users on YouTube in combination with the platform’s algorithm. Interestingly, 7 out of 50 clusters are characterised by what may be seen as a ‘situational’ culture of music reception by digital audiences. Such culture is not so much founded on music genres as traditionally conceived, but rather on the purposes of reception which are rooted in the context where this takes place.

Report: Exposure to Tobacco and Alcohol Content in YouTube Music Videos in Britain

Children and Young People NowVol. 2016, No. 3 Resources ResearchReport: Exposure to Tobacco and Alcohol Content in YouTube Music Videos in BritainJo Cranwell, Magdalena Opazo-Breton, John BrittonJo CranwellSearch for more papers by this author, Magdalena Opazo-BretonSearch for more papers by this author, John BrittonSearch for more papers by this authorJo Cranwell; Magdalena Opazo-Breton; John BrittonPublished Online:4 Dec 2017https://doi.org/10.12968/cypn.2016.3.26AboutSectionsView articleView Full TextPDF/EPUB ToolsAdd to favoritesDownload CitationsTrack Citations ShareShare onFacebookTwitterLinked InEmail View article FiguresReferencesRelatedDetails 2 February 2016Volume 2016Issue 3ISSN (print): 1755-8093ISSN (online): 2515-7582 Metrics History Published online 4 December 2017 Published in print 2 February 2016 Information© MA Education LimitedPDF download

Adult and adolescent exposure to tobacco and alcohol content in contemporary YouTube music videos in Great Britain: a population estimate

BackgroundWe estimate exposure of British adults and adolescents to tobacco and alcohol content from a sample of popular YouTube music videos.MethodsBritish viewing figures were generated from 2 representative online national...

Adolescents' exposure to tobacco and alcohol content in YouTube music videos.

AimsTo quantify tobacco and alcohol content, including branding, in popular contemporary YouTube music videos; and measure adolescent exposure to such content.DesignTen‐second interval content analysis of alcohol, tobacco or electronic cigarette imagery in all UK Top 40 YouTube music videos during a 12‐week period in 2013/14; on‐line national survey of adolescent viewing of the 32 most popular high‐content videos.SettingGreat Britain.ParticipantsA total of 2068 adolescents aged 11–18 years who completed an on‐line survey.MeasurementsOccurrence of alcohol, tobacco and electronic cigarette use, implied use, paraphernalia or branding in music videos and proportions and estimated numbers of adolescents who had watched sampled videos.FindingsAlcohol imagery appeared in 45% [95% confidence interval (CI) = 33–51%] of all videos, tobacco in 22% (95% CI = 13–27%) and electronic cigarettes in 2% (95% CI = 0–4%). Alcohol branding appeared in 7% (95% CI = 2–11%) of videos, tobacco branding in 4% (95% CI = 0–7%) and electronic cigarettes in 1% (95% CI = 0–3%). The most frequently observed alcohol, tobacco and electronic cigarette brands were, respectively, Absolut Tune, Marlboro and E‐Lites. At least one of the 32 most popular music videos containing alcohol or tobacco content had been seen by 81% (95% CI = 79%, 83%) of adolescents surveyed, and of these 87% (95% CI = 85%, 89%) had re‐watched at least one video. The average number of videos seen was 7.1 (95% CI = 6.8, 7.4). Girls were more likely to watch and also re‐watch the videos than boys, P < 0.001.ConclusionsPopular YouTube music videos watched by a large number of British adolescents, particularly girls, include significant tobacco and alcohol content, including branding.

Seeing Sound: Perhaps Love, YouTube, and Hong Kong's Cultural Convergence

Here I explore the relations between aural production, visuality and being, as they connect to the new identities that are formed through Hong Kong's production of Mandarin Chinese-language music, films and music videos. To explore these issues I focus on the movie Perhaps Love (Ruguo Ai) [P. Chan 2005] and YouTube music videos relating to that film. Hong Kong has a long-standing historical symbiosis between its music and movie industries. Perhaps Love includes a range of cultural metaphors that include Buddhist allegory as well as the interplay of cultural understandings of gender and geographical space. Seeing Hong Kong productions is both a form of knowing and of creative appropriation—for the movie makers, for the audience, and for fans who create their own narratives with the new tools that are available to them.

Viewers' Perceptions of a YouTube Music Therapy Session Video

Recent research revealed diverse content and varying levels of quality in YouTube music therapy videos and prompted questions about viewers' discrimination abilities. This study compares ratings of a YouTube music therapy session video by viewers with different levels of music therapy expertise to determine video elements related to perceptions of representational quality. Eighty-one participants included 25 novices (freshmen and sophomores in an introductory music therapy course), 25 pre-interns (seniors and equivalency students who had completed all core Music Therapy courses), 26 professionals (MT-BC or MT-BC eligibility) with a mean of 1.75 years of experience, and an expert panel of 5 MT-BC professionals with a mean of 11 years of experience in special education. After viewing a music therapy special education video that in previous research met basic competency criteria and professional standards of the American Music Therapy Association, participants completed a 16-item questionnaire. Novices' ratings were more positive (less discriminating) compared to experienced viewers' neutral or negative ratings. Statistical analysis (ANOVA) of novice, pre-intern, and professional ratings of all items revealed significant differences p, .05) for specific therapy content and for a global rating of representational quality. Experienced viewers' ratings were similar to the expert panel's ratings. Content analysis of viewers' reasons for their representational quality ratings corroborated ratings of therapy-specific content. A video that combines and clearly depicts therapy objectives, client improvement, and the effectiveness of music within a therapeutic intervention best represent the music therapy profession in a public social platform like YouTube.