Taste and the algorithm

Today, a consistent part of our everyday interaction with art and aesthetic artefacts occurs through digital media, and our preferences and choices are systematically tracked and analyzed by algorithms in ways that are far from transparent. Our consumption is constantly documented, and then, we are fed back through tailored information. We are therefore witnessing the emergence of a complex interrelation between our aesthetic choices, their digital elaboration, and also the production of content and the dynamics of creative processes. All are involved in a process of mutual influences, and are partially determined by the invisible guiding hand of algorithms. With regard to this topic, this paper will introduce some key issues concerning the role of algorithms in aesthetic domains, such as taste detection and formation, cultural consumption and production, and showing how aesthetics can contribute to the ongoing debate about the impact of today’s “algorithmic culture”

Taste or Addiction?: Using Play Logs to Infer Song Selection Motivation

Online music services are increasing in popularity. They enable us to analyze people's music listening behavior based on play logs. Although it is known that people listen to music based on topic (e.g., rock or jazz), we assume that when a user is addicted to an artist, s/he chooses the artist's songs regardless of topic. Based on this assumption, in this paper, we propose a probabilistic model to analyze people's music listening behavior. Our main contributions are three-fold. First, to the best of our knowledge, this is the first study modeling music listening behavior by taking into account the influence of addiction to artists. Second, by using real-world datasets of play logs, we showed the effectiveness of our proposed model. Third, we carried out qualitative experiments and showed that taking addiction into account enables us to analyze music listening behavior from a new viewpoint in terms of how people listen to music according to the time of day, how an artist's songs are listened to by people, etc. We also discuss the possibility of applying the analysis results to applications such as artist similarity computation and song recommendation.Comment: Accepted by The 21st Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2017

Methodological considerations concerning manual annotation of musical audio in function of algorithm development

In research on musical audio-mining, annotated music databases are needed which allow the development of computational tools that extract from the musical audiostream the kind of high-level content that users can deal with in Music Information Retrieval (MIR) contexts. The notion of musical content, and therefore the notion of annotation, is ill-defined, however, both in the syntactic and semantic sense. As a consequence, annotation has been approached from a variety of perspectives (but mainly linguistic-symbolic oriented), and a general methodology is lacking. This paper is a step towards the definition of a general framework for manual annotation of musical audio in function of a computational approach to musical audio-mining that is based on algorithms that learn from annotated data. 1

Social music in cars

This paper builds an understanding of how music is currently experienced by a social group travelling together in a car - how songs are chosen for playing, how music both reflects and influences the group’s mood and social interaction, who supplies the music, the hardware/software that supports song selection and presentation. This fine-grained context emerges from a qualitative analysis of a rich set of ethnographic data (participant observations and interviews) focusing primarily on the experience of in-car music on moderate length and long trips. We suggest features and functionality for music software to enhance the social experience when travelling in cars, and prototype and test a user interface based on design suggestions drawn from the data

The Usage of Personal Data as Content in Integrated Marketing Communications

Personal user data has proven extremely valuable for firms in the digital age. The wealth of data available to firms has provided unprecedented access into the world of the consumer. Companies hoping to capitalize on their user's data have turned to several interesting outlets. This research addresses the repurposing of user data as content in marketing. By analyzing four cases of data presented as marketing communications across two companies, this research provides new insights into the public release of private user data for marketing purposes. Four cases of personal data used in marketing communications were chosen specifically for their time proximity, characteristics of the sending firms, and their disparate outcomes. These instances of marketing communications, two by Spotify and two by Netflix, were released during November and December of 2017 and each resulted in a diverse range of public opinion. An analysis of these cases was conducted using the comprehensive framework of integrated marketing communications (Tafesse & Kitchen, 2017). There is a significant difference in the perceptual outcomes of integrated marketing communication campaigns which display user data as content. This analysis provides insights into the characteristics of marketing communications and how their outcomes fit into broader marketing strategies. These case studies provide opportunities for marketers to improve their campaigns in line with their desired audience outcome. Patterns of scope, strategy, mode, and outcome do not suggest success or failure in the context of marketing communications, but rather a set of insights marketers should keep in mind when pursuing communication strategies which harness personal user data.No embargoAcademic Major: Marketin

Social representation of “loud music” in young adults: A cross-cultural study

Background: Exposure to recreational noise, particularly music exposure, is considered one of the biggest public health hazards of our time. Some important influencing factors such as socioeconomic status, educational background, and cross-cultural perspectives have previously been found to be associated with attitudes toward loud music and the use of hearing protection. Although culture seems to play an important role, there is relatively little known about how it influences perceptions regarding loud music exposure in young adults. Purpose: The present study was aimed to explore cross-cultural perceptions of and reactions to loud music in young adults (18‐25 yr) using the theory of social representations. Research Design:The study used a cross-sectional survey design. Study Sample: The study sample included young adults (n = 534) from five different countries (India, Iran, Portugal, the United States, and the United Kingdom) who were recruited using convenience sampling. Data Collection and Analysis: Data were collected using a questionnaire. Data were analyzed using a content analysis, co-occurrence analysis, and also χ2 analysis. Results: Fairly equal numbers of positive and negative connotations (∼40%) were noted in all countries. However, the χ2 analysis showed significant differences between the countries (most positive connotations were found in India and Iran, whereas the most negative connotations were found in the United Kingdom and Portugal) regarding the informants’ perception of loud music. The co-occurrence analysis results generally indicate that the category “negative emotions and actions” occurred most frequently, immediately followed by the category “positive emotions and actions.” The other most frequently occurring categories included “acoustics,” “physical aliment,” “location,” and “ear and hearing problems.” These six categories formed the central nodes of the social representation of loud music exposure in the global index. Although some similarities and differences were noted among the social representations toward loud music among countries, it is noteworthy that more similarities than differences were noted among countries. Conclusions: The study results suggest that “loud music” is perceived to have both positive and negative aspects within society and culture. We suggest that the health promotion strategies should focus on changing societal norms and regulations to be more effective in decreasing the noise- and/or music-induced auditory symptoms among young adults

Henri Lefebvre and the Production of Music Streaming Spaces

This paper demonstrates how Henri Lefebvre's influential theory of the "production of space" can help generate a more critical understanding of transformations in digital music, and in particular, the emergence of data-driven and cloud-based music streaming services. Lefebvre distinguished between "social space" and what he calls "abstract space" - the space of capitalism. Music streaming services such as Spotify, Deezer, and Pandora, can be understood as the latest stage in the ongoing struggle to transform the "social space" of P2P file-sharing into "abstract space." By giving careful consideration to perceived, conceived and lived processes in the production of space - what Lefebvre called the "trialectics of space" - this paper illuminates the different ways music streaming services and their listeners produce new spaces of music consumption, helping us in turn to develop a more robust critique of abstract space in general