Music Consumption Research Articles

Reframing the filter bubble through diverse scale effects in online music consumption

The impact of platforms’ algorithmic curation devices on users’ consumption diversity has long since been the subject of debate in popular culture and academia alike. In recent years, methods to concretely appraise this debate have taken a comparative turn, with emerging research strands seeking to assess the influence of algorithmic recommendations relative to users’ organic behaviour (i.e. those with a relative lack of algorithmic influence). Nevertheless, as the contribution of this work clearly shows, contradictory findings that algorithmic devices may both foster “bubbly” confinement dynamics and diverse exploration appear to stem, at least in part, from tensions surrounding information representation and scale. Taking into account various scales, affordances, and diversity measures, the contribution of this work conducts an empirical analysis of approximately 50,000 Deezer users’ artist consumption histories across different affordances offering various degrees of algorithmic assistance. Transitioning through three scales of increasing aggregation—intra-sessions, inter-sessions and inter-affordances—our work underscores how shifts in perspective, particularly in information representation, can yield markedly different conclusions concerning the role of algorithmic devices in fostering diversity. However, when considered collectively, these perspectives coalesce to provide a nuanced update to the seminal filter bubble narrative: algorithmic curation devices may introduce more novelty than what users’ achieve organically, yet concurrently, this novelty is more semantically confined. Consequently, our research significantly contributes towards an enriched understanding of the intricate dynamics surrounding on-platform algorithmic devices.

Adolescent Identity Construction and Communication Through Music Consumption in Virtual Space

Adolescent Identity Construction and Communication Through Music Consumption in Virtual Space

‘A distant echo attracts me, fragrance of life beyond’: growing up a metalhead in India

ABSTRACT The paper is an account of growing up a metalhead in a suburb of a city in south Gujarat and then in Kolkata. The paper situates the author’s experience of growing up in a suburb of a non-metropolitan city in India as a metalhead and eventually moving to metropolitan spaces to access spaces of music consumption. The paper travels across the cities of Surat, Kolkata, Hyderabad, Pune, Mumbai and Bengaluru to narrate the heavy metal scene that was present at the turn of the noughties, from 2006 to 2013. The paper also dwells on the role of the personal computer, pirate consumption, class, geographies of live music, fuzzy contours of ‘western music’, and the peculiarity of heavy metal in Kolkata.

AN ALGORITHMIC EVENT: THE CELEBRATION AND CRITIQUE OF 'SPOTIFY WRAPPED'

Each year, Spotify encourages its users to share aesthetically pleasing data stories ‘wrapped’ and repackaged from their listening behaviour. We approach ‘Wrapped’ as an ‘algorithmic event’, defined as a moment in time in which there is a collective orientation towards a particular algorithmic system and associated data. To examine how people make sense of ‘Wrapped’ as an algorithmic event, we bring together ordinary Spotify users to explore datafication through a series of prompts and creative activities, including a modified version of the ‘walkthrough’ (Light et al., 2018) and a craft-based exercise. These exercises allow participants to tease out how normative assumptions are baked into ‘Wrapped’ and mobilise particular understandings of individuals, their habits, tastes and identities. Importantly, we position our participants as co-analysts, following the work of Robards and Lincoln (2017) and Markham (2021), and in our analysis highlight themes that arise from their contributions. Emerging findings allude to highly ambivalent feelings towards ‘Wrapped’ as an algorithmic event: Our participants both celebrate and critique how Spotify claims to ‘know’ them as individuals. They also contest the way ‘Wrapped’ is framed as revealing the ‘truth’ about music consumption and taste. As such, we argue that algorithmic events like ‘Wrapped’ are useful ways to think through data capture and algorithmic systems. The phenomenon of ‘wrappification’ – by which we mean the repackaging of behavioural data that captures a particular activity throughout the year and the responses to the belief that we can ‘know’ ourselves in this way – speaks to such impact.

Rethinking Materiality of Music: The Transformative Practices of Music Streaming

This study examines the evolving materiality of music in the streaming era, arguing that music’s materiality in streaming contexts is not fixed and predefined, but a dynamic and relational phenomenon emerging through the interplay of user practices, technological affordances and cultural meanings. Drawing on qualitative interviews and online ethnography with indie music enthusiasts in China, the research explores two key aspects of streaming music consumption to examine music’s materiality: playlisting practices and users’ reflexive interactions with recommendation algorithms. The findings reveal a co-evolutionary relationship between user practices and technological affordances, where both users and algorithms actively shape the experience and materiality of music. Playlist curation emerges as a new form of meaning-making, transforming intangible streaming music into personalised, structured objects; while user-algorithmic interplay creates a dynamic environment where music perception and engagement are constantly negotiated. These cases illuminate a new perception of music materiality – one that is constantly emergent and relationally constituted. The article contributes to broader debates on the digitalisation of culture, the changing nature of cultural consumption, and the role of technology in shaping cultural experiences. It invites a re-examination of the concept of materiality in the context of digital platforms.

Taste externalization practices among Brazilian metal consumers who learn to play musical instruments

We consider music consumption an integrative practice that promotes taste, in which consumers of a specific musical genre are occasionally interested in learning to play a musical instrument. In this context, the article analyzed the interrelationships between practice and taste externalized among Brazilian consumers of metal music and related subgenres. We conducted interviews to understand how self-taught instruction, formal music education and musical instruments configure the process. Self-taught instruction is based on listening/technical skills enhanced by informal pedagogical resources, in which the performance of metal artists also influences the song reproduction. Formal music education is guided by traditions and methods rather than focusing solely on the learner’s taste; however, it is a path for ‘authorial experiments’ that externalize the preference for metal music. Musical instruments influence this process due to their technical specifications, electronic equipment and aesthetic elements. We concluded that the learning process to play musical instruments constitutes a taste externalization practice and that the way it occurs is associated with metal music consumption in the researched context.

Exploring the Relevance of Values Generated by Music Organisations in Consumers

Abstract The digital revolution has significantly changed the way music is consumed, particularly among young people. This technological transformation, coupled with economic and sociocultural shifts, has heightened interest in studying music consumption across various scientific disciplines. However, the identity of music consumers, demographic influences and the diversity of consumption in today’s context remain areas ripe for exploration. To contribute to this line of inquiry, this paper employs the arts and cultural organisation (ACO) model (Addis & Rurale 2021) to conduct exploratory research on music values from the consumer perspective. An electronic survey was utilised as the data gathering technique among music listeners. The results highlight the significance of music in fostering personal joy and creating community, along with the considerable value attributed to music as a catalyst for discussion and innovation. Moreover, the well-being value is associated with entertainment, joy and relaxation derived from listening to music. Finally, age emerges as a variable capable of elucidating trends in the assessment of creativity and well-being values.

The Influence of Tiken Jah Fakoly’s Reggae Music in Post-independence Côte d’Ivoire

Tiken Jah Fakoly, a prominent Ivoirian reggae artist, has played an important role in the social and political development of post-independence Côte d’Ivoire. This paper explores the impact and influence of Tiken Jah Fakoly’s music on the socio-political dynamics of the country, especially as these relate to national unity, political awareness, and social movements. To assess Fakoly’s influence on the social fabric of Côte d’Ivoire, we administered a questionnaire-based survey to a diverse sample of participants. The questions included information on demographics, music consumption habits, familiarity with Fakoly’s music, perceptions of his recordings, his influence of their sense of identity, and their impressions of the impact his music has on social and political issues. The results show that Tiken Jah Fakoly’s music has had a significant effect on the attitudes of Ivoirians and has helped shape the unique character of Ivorian reggae. His music has fostered a sense of unity and solidarity among Ivorians, and it has inspired numerous individuals to take part in advocacy and activism-related activities. The outcomes of this research have broad implications for the role African music plays in nation-building processes, in the creation of a sense of cultural identity, and in the capacity to motivate political and social movements.

Satisfied But No Payment: The Impact of Perceived Value on Continuance Intention and Purchase Intention in Music Streaming Services

The prevalence of digital music streaming has changed the way people listen to music. Over the past few years, digital music has developed, and streaming music over the Internet is a popular way people listen to music. While many reports focus on digital music and music piracy innovations, only a few applications in economic analysis in terms of the customer's willingness to pay for music services should be considered, especially in Thailand, where the country's digital infrastructure has been developing. This study presents the factors influencing perceived value and purchase intention towards music streaming in Thailand with an extended technology acceptance model and a deep understanding of users’ perceived value, satisfaction, and continuance intention in the Thai context. The research investigates future purchase intentions among freemium and premium users, providing a comprehensive view of potential consumer behavior in the music streaming market. The proposed model was empirically evaluated using an online questionnaire-based survey of 443 respondents about the perceived use of music streaming services in Thailand. Structural Equation Modelling (SEM) technique was used to analyze the data. The results indicated that perceived usefulness, perceived ease of use, and perceived enjoyment were directly and positively correlated with perceived value. Besides, perceived value was directly and positively correlated with satisfaction, continuance intention, and purchase intention. Regardless, satisfaction and continuance intention could not predict purchase intention significantly. In the Thai context, consumer satisfaction and continuance intention with music streaming in Thailand are not a good driving factor in suggesting purchase intention. Furthermore, music streaming content, users’ emotional responses, and feelings play a crucial role in the decision to use and subscribe. The results provided further insight into music application market trends and built an understanding of Thai music consumer behavior.

Impacts of AI on Music Consumption and Fairness

The algorithmic systems utilized by music streaming services have the potential to positively influence individual choices by promoting new artists, but they are also often accused of perpetuating biases. In this research note, we aim to explore the impact of these platforms’ AI-based algorithms on fairness in music consumption. To address this question, we adopt a multidimensional approach that considers the legal, economic, and algorithmic dimensions of fairness. This approach is applied to our EU Horizon Europe Fair MusE project, which advocates for a fairer music ecosystem. However, it should be noted that we propose a tool to score output (playlists) based on fairness models instead of directly altering the algorithms. Data from end users, data brokers, and open-source databases will inform the model, while the processing of the data is aimed at providing users with insights into algorithmic biases and empower them to influence the output. Acknowledging this aspect, this research note serves as a prelude to highlight the need for increased transparency and explainability of algorithms. Furthermore, we seek to inform policy interventions that promote fairness, particularly regarding data sharing between creators and platform providers. Such interventions would foster trust among stakeholders and benefit both users and businesses.

Young consumers' online experiential consumption behavior of foreign contemporary music: generational and gender differences in the refined stimulus-organism-response theory

PurposeThis study aims to examine the younger generations’ experiential consumption of foreign contemporary music online (i.e. digital music streaming services) by generation and gender in the US market.Design/methodology/approachThe author proposes a sequential experiential consumption model by applying Jacoby’s refined stimulus-organism-response (S-O-R) theory to better understand the experiential sequences in foreign music consumption among young generations in the US market. The proposed model, using structural equation modeling (SEM), examines a cognitive permeable role and a hierarchical affective mediating role. Also, moderating roles of generation and gender are simultaneously tested in overall and specific causal relationships.FindingsThe refined S-O-R framework is superior to a linear one in better understanding young consumers’ online experiential foreign music consumption behavior. Moreover, hierarchical sequenced affective organismic behavior is crucial to enhance young consumers’ online music consumption experiences to regulate subsequent behavioral responses. Furthermore, gender differences but no generational differences exist in the experiential consumption process among young consumers. Nevertheless, the strength of S-O-R factors affecting experiential consumption seems idiosyncratic simultaneously in gender and generation.Practical implicationsThe study suggests foreign music streaming services boost profitability by focusing on young consumers' psychological ownership and tailored experiences, encouraging a shift from freemium to premium subscriptions. Also, the findings recommend adopting phygital experiences using technologies like AR, VR and MR to enhance engagement and create unique, emotionally resonant experiences for young consumers, thus fostering a more profitable business model.Originality/valueThe authors address under-researched topics relevant to young generations by applying Jacoby’s refined S-O-R framework to foreign music consumption through online streaming. This approach delves into a lesser-explored consumer behavior framework, highlighting young generations’ musical trends. The model reveals cognitive and affective roles, offering advantages over traditional linear S-O-R models. It also uniquely incorporates the moderating effects of generation and gender in music consumption studies, addressing a gap in music-related studies.

Towards an Understanding of the Music Value Chain in Ghana: The Role of Artiste Managers

The Ghana music value chain pivots on the dynamics of the artiste managers who handle the various music genres. Unfortunately, studies on artiste managers, the types of artiste managers, and a detailed description of their training, and general operations are rare in the Ghanaian context. Hence, this study was conducted to shed light on the significant roles of artiste managers for a better understanding of the Ghanaian music value chain. The research used a triangulated approach (qualitative and quantitative) to collect data. The primary research method employed was qualitative through semi-structured interviews (face-to-face and telephone as well as video calls). The quantitative method was employed mainly as a secondary source from the MUSIGA-KPMG Report (2014) among others. The results showed that different types of artiste managers in Ghana are found across different genres captured in the music value chain. These artiste managers are key at the marketing stage of the music value chain. Thus, performance is used as a channel to convey the music of the artiste to the music consumers. Based on the results, it is recommended that the government enact policies that streamline music skills development by making music apprenticeships attractive. This can be done by supporting ongoing efforts by private institutions to develop the artiste. Thus, a public-private partnership is a laudable approach that has far-reaching implications in creating artistes in the country. The study offers useful information that may contribute to nurturing and developing the artiste for social and economic gains. Keywords: Artiste Managers, Creative Art Industry, Music Value Chain, Ghana

The population of Veneto faced with technological consumption of music during the pandemic.

This work is the result of one of the lines of research opened in the LabinTic group (UCLM) and a stay in the city of Padua, in the Italian Veneto area, in 2022. After observing the side effects in Italy as a result of COVID-19 and the Great Lockdown, we wanted to know in more depth some aspects related to how the people of Veneto used IT as an important weapon to fight against forced isolation and, if possible, compare this with other similar studies performed in Castilla-La Mancha. To achieve this objective, an ad hoc questionnaire was designed and validated through expert judgment. This questionnaire was administered to a random probabilistic sample by disseminating it through social media and email using the "snowball" method. A total of 338 people who comprised the population sample of the study (n = 338) were obtained. After analyzing the data through SPSS 28, using a mixed methodology considering qualitative and quantitative aspects, the great influence that IT had among the Italian population during the lockdown common aspects of their everyday lives and incorporating some acquired habits (listening to music, for example) into their usual life routines after the return to normality was determined among other features and assessments. In summary, the text highlights how the pandemic influenced music consumption, the popularity of different music genres, the role of social media, and the enduring importance of the music itself in people's lives. It suggests that music remains a source of comfort and entertainment in challenging times.

The influence of homophily and social identity on eWOM in streaming consumption behaviour

Purpose The purpose of this paper is to identify the influence of homophily and social identity in eWOM adoption and influence on music consumption in streaming platforms. The study also proposes a framework for eWOM influence on product consumption. Design/methodology/approach Data were collected through an electronic questionnaire with a total of 524 valid responses. A partial least square methodology was used to approach the data analysis. Findings The findings indicate that both homophily and social identity have an influence on eWOM effect. Additionally, homophily shows influence on social identity being an important value to the total influence. It is also confirmed how eWOM has direct influence on music consumption. Practical implications Social information of consumers becomes more relevant than ever, as the results contribute to highlight its importance as a message adoption influencer and product consumption driver. Originality/value This study contributes to social communication theory by identifying homophily and social identity as valuable assets during eWOM generation. The research brings a new angle to social identity theory in the social network environment and influences eWOM adoption in music streaming consumption.

Exploring music listening patterns: an online survey

An online survey was carried out to explore how respondents listen to music recordings. It was anticipated that the listener’s preferences would be influenced by various factors, such as age, music genre, the contexts in which they listen, and their favored methods of music consumption. Consequently, the data were collected to analyze these relationships. The survey, structured as a web application, encompassed 23 questions, with seven specifically aimed at defining the respondents and the remainder contributing to the dataset for analysis. The results reveal a prevailing preference for listening to music via streaming platforms. Respondents predominantly engage in passive listening, where music becomes a background presence without commanding their focused attention. Moreover, the data also highlight a noteworthy correlation between preferred music genres and the age of the listeners.

A Utility Function for the Music Consumer Based on their Emotional Responses

A Utility Function for the Music Consumer Based on their Emotional Responses

유튜브 댓글 분석을 통한 클래식 음악 시청자 반응 연구

This study analyzed Korean-language comments on YouTube videos of pianist Lim Yunchan’s performance of Rachmaninoff’s Piano Concerto No. 3 during the 2022 Van Cliburn International Piano Competition finals, exploring domestic viewers’ reactions and emotional perceptions of classical music. The research methodology involved selecting only Korean comments collected via the YouTube Data API from June 20, 2022, to December 1, 2023, refining the data, and conducting keyword frequency analysis, LDA Topic Modeling, and sentiment analysis using R. The analysis indicated that viewers expressed deep emotional resonance and admiration for the artistic excellence of Lim’s performance through the identified keywords. The LDA Topic Modeling yielded three themes: ‘the Van Cliburn Competition’, ‘viewer responses’, and ‘the bright future of K-Classic’. Although the sentiment analysis showed some limitations, predominantly positive responses were observed. This study provides substantive data on how viewing classical music performances on YouTube can elicit emotional resonance and admiration for artistic excellence in viewers. Additionally, it confirmed that YouTube plays a crucial role in enhancing the accessibility of classical music and serving as a conduit for appreciation and communication. This research contributes to understanding the current landscape of Korea’s classical music consumption and offers insights into the consumption patterns of classical music in the digital media era.

Song Recommendation System Based on Facial Emotion

This research is aiming to enhance the user experience in music consumption by incorporating real-time facial emotion analysis. Emotions play a fundamental role in shaping individual preferences, and leveraging facial expressions as a means of understanding user’s emotional states can significantly contribute to personalized music recommendations. Our proposed system begins by capturing real-time facial expressions using a webcam or analyzing static images. These facial expressions are then processed through a CNN-based emotion recognition model trained to classify emotions such as happiness, sadness, anger, and more. The CNN model extracts high-level features from facial images, enabling accurate emotion recognition. Using the detected emotional state as input, our system employs a recommendation algorithm tailored to the user's current emotional state to suggest relevant music or videos from YouTube.

Music Information Retrieval using Deep Learning Techniques

Music Information Retrieval (MIR) is gaining attention due to the surge in digital music and the need for efficient search and recommendation systems. Traditional MIR methods rely on hand-crafted features and rule-based systems, limiting their adaptability. Deep Learning (DL) shows promise in automatically extracting complex patterns from raw data. This paper offers an extensive overview of MIR tasks like classification, genre recognition, similarity search, and recommendation, along with DL models like Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), including LSTM and Transformer architectures, tailored for MIR. Challenges such as data scarcity, computational complexity, and interpretability persist, with proposed solutions like data augmentation, transfer learning, and attention mechanisms. Experimental results on benchmark datasets demonstrate DL's superiority in accuracy, scalability, and robustness over traditional methods. Practical examples highlight DL's potential to revolutionize music search, recommendation, and analysis. Emphasizing the importance of large annotated datasets for training high-quality DL models, strategies for data collection, labeling, and preprocessing are outlined. DL offers promising prospects for advancing MIR by addressing its inherent challenges and establishing new performance benchmarks. Further DL development is expected to drive innovation and enhance digital music consumption experiences through MIR systems. Keywords: Deep Learning, Convolution Neural Network (CNNs), Recurrent Neural Network (RNNs), Digital Music Consumption, Genre recognition.

Dynamic Playlist Generation using Machine Learning

This study investigates the application of machine learning algorithms for dynamic playlist generation in the context of music recommendation systems. The traditional method of creating playlists frequently depends on immutable standards, like artist or genre, which might not adequately represent the unique and dynamic character of personal preferences. On the other hand, our suggested system makes use of machine learning methods to examine user behavior, preferences, and contextual elements in order to create playlists that are dynamically created and customized to each user’s individual preferences. In order to train machine learning models, the study collects user interaction data, such as listening history, skip patterns, and user feedback. To extract patterns and relationships from the data, a variety of algorithms are used, including hybrid models, content-based filtering, and collaborative filtering. After that, the models are incorporated into a dynamic playlist creation system that can eventually adjust to changing user preferences.Our test findings show how well the suggested strategy works to improve user experience by offering more interesting and customized playlists. With its ability to adjust to changing user preferences and contextual cues, the dynamic playlist generation system provides a smooth and pleasurable music discovery experience. We also talk about possible enhancements, implementation difficulties, and deployment considerations in the real world.This work adds to the ongoing efforts to improve music recommendation systems by demonstrating how machine learning can be used to develop more responsive and intelligent playlist generation systems. The results highlight how crucial customized experiences are in the constantly changing world of digital music consumption. Index Terms—hybrid mode, content-based filtering, intelligent playlist, music