Music Consumption Research Articles

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.

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

Review Paper: Music Player Website

In an age described by means of digital connectivity and the insatiable need for Music, the role of Music websites has turn out to be an increasing number of crucial. This article provides a top-level view of the improvement, design, technology and user experience of Music web sites and explores their important area in today's tune industry. It takes a historical angle and lines the course from the early days of on-line streaming services to the advanced platforms operating today. The dialogue delves into the intricacies of person interface design, specializing in factors such as navigation, playlists, and recommendation algorithms that beautify the person enjoy. Additionally, this article examines the era and explains the backend, backend, and analytics that support these structures. Understanding the complexities of track streaming requires cautious consideration of prison and ethical issues, together with copyright and artist compensation. Through information research and analysis, this text highlights tendencies and rising problems, providing insight into the future of the track website. Finally, this looks at highlights the important position music web sites play in permitting us to discover, consume and interact with song in the digital age. Keywords- Music player websites, Digital music consumption, Online streaming services, User interface design, Recommendation algorithms, Technology stack, Frontend frameworks, Backend languages, Copyright laws, Artist compensation

DESIGN AND IMPLEMENTATION OF EMOTION BASED MUSIC RECOMMENDATION SYSTEM

Internet has bought numerous changes into our day- to- day life. As part of it, life changes in people took place. Unhealthy cultures, Unhealthy relations among people, and Irregular sleep touched off internal issues and to fight these problems people use the internet as an escape. The Internet has made our lives simpler by furnishing a plethora of apps and services, backed in carrying instant communication and numerous further. Entertainment consumption from the Internet especially music helps in dwindling stress, anxiety, or depression. harkening to right music at the right time improves internal health. To make music consumption accessible we're developing a System that plays music applicable to the stoner’s emotion. stoner’s emotion can be detected by facial expressions. These expressions can be captured from the camera. Machine literacy/ Deep literacy provides colorful ways to descry mortal emotion. One similar fashion is CNN with Keras, which generates a small size trained model. Our proposed emotion- grounded music player system using CNN performs real time emotion discovery and plays a suitable song. It can be an fresh point to being music players in our bias. By suggesting suitable song to honored emotion druggies satisfaction can be bettered. Keywords: Machine Learning/Deep Learning, CNN with Keras, real time

The Soundtrack of a Crisis: More Positive Music Preferences During Economic and Social Adversity

This paper studies the positiveness in most consumed songs during a period of sadness, worry and uncertainty: the COVID-19 crisis in comparison with previous years. In order to perform the analysis, we create an original positive music indicator using a dataset of weekly patterns for music consumption in 31 OECD countries over a five year period. Results show that negative shocks from events such as economic business cycles and the COVID-19 pandemic increase the consumption of positive songs, suggesting that society compensates the negative impact on well-being with positive music. We conclude that society adapts sentiment-based music consumption preferences according to the socioeconomic situation.

Formatted Sound

Formatted Sound

Auditory Learner

Auditory Learner

Music consumption and uses in Japan

This research investigates the relationship between music consumption and cultural dimensions within a Japanese context. Since Japan is the second largest music market globally, it is surprising that there is little focus on those factors often examined in cross-cultural research that might mean Western findings do not extrapolate well. A questionnaire using established measures of tightness–looseness, relational mobility, and ideal affect was used to test three main research questions. RQ1 was that there should be a relationship between cultural dimensions and musical taste, and this was fully supported. RQ2 was that cultural dimensions should relate to participants’ goals of music consumption, and this was largely supported. RQ3 was that there should be a relationship between socioeconomic status and musical taste, but this was not supported. The findings also supported several more specific research questions concerning how specific uses of music ought to relate to specific cultural dimensions. The findings of the study help us better understand the way music is consumed in relation to specific cultural dimensions in the context of Japan and beyond. It also extends the literature concerning music and cross-cultural psychology where prior research has not considered these dimensions within the context of music consumption.

Comparative Study of the Pop Music Industry in China and the United States

The pop music industry has a wide-ranging social influence and serves as an important medium for cultural exchange and international dissemination. This article aims to conduct a comparative study of the pop music industries in China and the United States, with the goal of comparing the differences and variations in pop music development between these two-major economic and cultural powers. Firstly, we compare and analyze the differences and similarities between the two countries in terms of music market size, music consumption patterns, and the value chain of the music industry. Secondly, we explore the challenges and opportunities faced by the pop music industries in China and the United States, aiming to inspire reflections on the development of the pop music industry in both countries. The study reveals that the future direction of China's pop music industry focuses on increasing the number of paying users and integrating pop music with social platforms. On the other hand, the U.S. pop music industry is dedicated to expanding into emerging overseas markets and enhancing its own influence. The future development trends of the pop music industry in China and the United States provide valuable insights for further exploration and promotion of the pop music industry's development.

Software review: What kind of music are you into? Collecting behavioral music consumption data in online surveys with Spotivey

Software review: What kind of music are you into? Collecting behavioral music consumption data in online surveys with <i>Spotivey</i>