Enacting music through paratexts : a shifting politics of interpretation

I engage with paratextual mediation of music through the lens set by Gérard Genette in Paratexts: Thresholds of Interpretation (1997). I theorize some of the ways different systems of paratexts shape acts of interpreting a musical text through a series of case studies in musical scores, CDs, and digital music. My final case study considers Spotify as exemplary of the changing conditions surrounding the relationship between text and paratext through Internet technology. Musical texts in Spotify bear a loosened relationship with their interacting paratexts as compared to scores and CDs; whereas a score presentation fixes these paratexts to a musical text by virtue of its materiality, the ways paratexts get attached to digital texts are diverse and highly fluid. Moreover, my case studies highlight the shifting relations of cultural power that lie behind these presentations of music through paratexts. Not all interpreters have the same agency to disseminate music through paratexts; with published scores, a select few hold an inordinate influence to frame interpretation for others in this way. Internet technology furnishes a shift in this cultural power, as more listeners gain more agency to affix paratexts to music in a way that can shape the listening experiences of others. Spotify presents music through paratexts by drawing on listener data, thereby democratizing a certain portion of this framing power to listeners. Even so, interpretation in Spotify is filtered through the network of technologies and actors representing Spotify's company, who perform a gatekeeping function on musical content through paratexts.Musi

O impacto dos algoritmos no consumo de música

Os Sistemas de Recomendação (RS) são definidos como algoritmos que classificam e recomendam produtos culturais a partir de dados sobre as práticas e o comportamento dos usuários.  O objetivo deste artigo é diagnosticar as consequências sociais e culturais dos algoritmos de recomendação de música como intermediários culturais on-line, examinando como e até que ponto eles afetam a percepção cultural, a classificação da música, a formação do gosto, o comportamento do ouvinte e a escolhas dos usuários. Realizamos uma revisão sistemática da literatura para identificar e discutir a produção científica sobre as implicações sociais e culturais de tais algoritmos nas práticas de consumo de música. Foram obtidos 311 artigos a partir de pesquisas bibliográficas em nove diferentes bases de dados científicos. Nossa análise crítica indicou quatro abordagens temáticas principais exploradas pela comunidade científica sobre esse tema entre 2000 e 2016: 1) O papel dos sistemas de recomendação na indústria fonográfica; 2) Impacto dos serviços de streaming no download de música; 3) Viés na classificação e recomendação de conteúdo; e 4) Consumo de música como recurso social. Os resultados revelam a lógica da intermediação cultural via sistemas de recomendação no mercado da música: esses algoritmos influenciam, modelam e mapeiam os gostos e hábitos dos usuários em um ambiente aparentemente livre, diversificado e ao mesmo tempo personalizado

El impacto de los algoritmos en el consumo de música: una revisión sistemática de literatura

Os Sistemas de Recomendação (RS) são definidos como algoritmos que classificam e recomendam produtos culturais a partir de dados sobre as práticas e o comportamento dos usuários.  O objetivo deste artigo é diagnosticar as consequências sociais e culturais dos algoritmos de recomendação de música como intermediários culturais on-line, examinando como e até que ponto eles afetam a percepção cultural, a classificação da música, a formação do gosto, o comportamento do ouvinte e a escolhas dos usuários. Realizamos uma revisão sistemática da literatura para identificar e discutir a produção científica sobre as implicações sociais e culturais de tais algoritmos nas práticas de consumo de música. Foram obtidos 311 artigos a partir de pesquisas bibliográficas em nove diferentes bases de dados científicos. Nossa análise crítica indicou quatro abordagens temáticas principais exploradas pela comunidade científica sobre esse tema entre 2000 e 2016: 1) O papel dos sistemas de recomendação na indústria fonográfica; 2) Impacto dos serviços de streaming no download de música; 3) Viés na classificação e recomendação de conteúdo; e 4) Consumo de música como recurso social. Os resultados revelam a lógica da intermediação cultural via sistemas de recomendação no mercado da música: esses algoritmos influenciam, modelam e mapeiam os gostos e hábitos dos usuários em um ambiente aparentemente livre, diversificado e ao mesmo tempo personalizado.Los sistemas de recomendación (SR) son definidos como algoritmos que clasifican y recomiendan productos culturales basados ​​en datos sobre las prácticas y el comportamiento de los usuarios. El propósito de este artículo es diagnosticar las consecuencias sociales y culturales de los algoritmos de recomendación musical como intermediarios culturales online, examinando cómo y en qué medida afectan la percepción cultural, la clasificación musical, la formación del gusto, el comportamiento del oyente y las eleciones de los usuario. Realizamos una revisión sistemática de literatura para identificar y discutir la producción científica sobre las implicaciones sociales y culturales de tales algoritmos en las prácticas de consumo de música. Fueran obtenidos 311 artículos por búsquedas bibliográficas en nueve bases de datos científicas diferentes. Nuestro análisis crítico indica cuatro enfoques temáticos principales explorados por la comunidad científica sobre este tema entre 2000 y 2016: 1) El papel de los sistemas de recomendación en la industria de la música; 2) Impacto de los servicios de streaming en la descarga de música; 3) Parcialidad en la clasificación y recomendación de contenido; y 4) Consumo de música como recurso social. Los resultados revelan la lógica de la intermediación cultural com el uso de los sistemas de recomendación en el mercado de la música: estos algoritmos influyen, modelan y mapean los gustos y hábitos de los usuarios en un ambiente aparentemente libre, diverso y al mismo tiempo personalizado.Recommendation Systems (RS) are defined as algorithms that classify and recommend cultural products based on data about users’ practices and behavior. The purpose of this research is to diagnose the social and cultural consequences of music recommendation algorithms as online cultural intermediaries, examining how and to what extent they affect cultural perception, music classification, taste formation, listener behavior and user choices. We conducted a systematic literature review to identify and discuss the scientific production on the social and cultural implications of such algorithms in music consumption practices. 311 articles were obtained from bibliographic searches in nine different scientific databases. Our critical analysis indicated four main thematic approaches explored by the scientific community on this topic between 2000 and 2016: 1) The role of recommendation systems in the music industry; 2) Impact of streaming services on music download; 3) Bias in the classification and recommendation of content; and 4) Consumption of music as a social resource. The results reveal the logic of cultural intermediation via recommendation systems in the music market: these algorithms influence, model and map the tastes and habits of users in an apparently free, diverse and personalized environment

Recommender systems as “tastemakers”: collaborative filtering as a market strategy for online cultural products

In the cultural market, the operation of which depends on the creation of intersubjective values to generate the production of consumers, the market strategies to adjust supply and demand have been historically characterised by mechanisms of social recommendation; a phenomenon that has intensified and changed on the Internet. The aim of this paper is to discuss the social conditions for the production of belief in symbolic goods and their applications in online markets. Pierre Bourdieu’s theory on the field of cultural production provides the conceptual grounding for the proposal of a theoretical study that compares traditional instances of symbolic goods recommendation and today’s online recommender systems. This analysis diagnoses the transformation of social processes of influence on online cultural consumption through collaborative filtering and identifies relevant topics for future research in the domain of cultural goods e-commerce

Towards a theoretical approach for analysing music recommender systems as sociotechnical cultural intermediaries

As the rate and scale of Web-related digital data accumulation continue to outstrip all expectations so too we come to depend increasingly on a variety of technical tools to interrogate these data and to render them as an intelligible source of information. In response, on the one hand, a great deal of attention has been paid to the design of efficient and reliable mechanisms for big data analytics whilst, on the other hand, concerns are expressed about the rise of 'algorithmic society' whereby important decisions are made by intermediary computational agents of which the majority of the population has little knowledge, understanding or control. This paper aims to bridge these two debates working through the case of music recommender systems. Whilst not conventionally regarded as 'big data,' the enormous volume, variety and velocity of digital music available on the Web has seen the growth of recommender systems, which are increasingly embedded in our everyday music consumption through their attempts to help us identify the music we might want to consume. Combining Bourdieu's concept of cultural intermediaries with Actor-Network Theory's insistence on the relational ontology of human and non-human actors, we draw on empirical evidence from the computational and social science literature on recommender systems to argue that music recommender systems should be approached as a new form of sociotechnical cultural intermediary. In doing so, we aim to define a broader agenda for better understanding the underexplored social role of the computational tools designed to manage big data

Matchmakers or tastemakers? Platformization of cultural intermediation & social media’s engines for ‘making up taste’

There are long-standing practices and processes that have traditionally mediated between the processes of production and consumption of cultural content. The prominent instances of these are: curating content by identifying and selecting cultural content in order to promote to a particular set of audiences; measuring audience behaviours to construct knowledge about their tastes; and guiding audiences through recommendations from cultural experts. These cultural intermediation processes are currently being transformed, and social media platforms play important roles in this transformation. However, their role is often attributed to the work of users and/or recommendation algorithms. Thus, the processes through which data about users’ taste are aggregated and made ready for algorithmic processing are largely neglected. This study takes this problematic as an important gap in our understanding of social media platforms’ role in the transformation of cultural intermediation. To address this gap, the notion of platformization is used as a theoretical lens to examine the role of users and algorithms as part of social media’s distinct data-based sociotechnical configuration, which is built on the so-called ‘platform-logic’. Based on a set of conceptual ideas and the findings derived through a single case study on a music discovery platform, this thesis developed a framework to explain ‘platformization of cultural intermediation’. This framework outlines how curation, guidance, and measurement processes are ‘plat-formed’ in the course of development and optimisation of a social media platform. This is the main contribution of the thesis. The study also contributes to the literature by developing the concept of social media’s engines for ‘making up taste’. This concept illuminates how social media operate as sociotechnical cultural intermediaries and participates in tastemaking in ways that acquire legitimacy from the long-standing trust in the objectivity of classification, quantification, and measurement processes