Som musikskapare har jag länge skrivit och producerat musik, men mycket av musiken har aldrig nått sin lyssnare. I denna uppsats har jag valt att skriva om hur processen kan se ut när ny musik ska publiceras och hur marknadsföringen kan se ut. Jag har samlat in data genom att intervjua verksamma inom musikbranschen samt. tagit del av ett podcastavsnitt och webbsidor. Jag har även använt mig av en exempellåt som jag själv varit med och skrivit. Genom processen har jag kommit fram till en analys av PR inom musikbranschen. Jag har tagit upp kommersiell musik, radio, Spotify, samarbeten mellan A&R:s och artister. De resultat jag kommit fram till genom intervjuerna visar även på hur ett kontrakt mellan ett musikbolag och en artist kan se ut. I slutsatsen tar jag upp att det finns många olika sätt att jobba med PR, antingen själv som artist eller med hjälp av ett musikbolag. Jag har även kommit fram till att kontrakt mellan artist och musikbolag kan se väldigt olika ut. Under rubriken Framtida Forskning skriver jag att det vore intressant att analysera vidare i ämnet och kanske gå in mer på siffror och statistik.

Denna uppsats syfte ligger i att skapa förståelse för var, när, och hur det är möjligt att uppnå en musikupplevelse som är koncentrerad med Spotify. Tre frågeställningar har tagits fram som behandlar: konstobjektets immateriella form, hur plats och mobilitet kan påverka upplevelsen, och hur detta möjliggör eller försvårar en koncentrerad musikupplevelse. Uppsatsens teoretiska ingång har sin utgångspunkt från Walter Benjamins (2014) tanke om att konsten besitter en aura som påverkas av form och mediering. För att förstå det strömmade musikmediet och konstobjektet används Jay David Bolter & Richard Grusins (1999) remedieringsteori, samt senare teorier om det personliga flödet av Richard Grusin (2009). Tillkommer gör även teorier om musikpraktiker i form av: Lee Marshall (2014) och Eric W. Rothenbuhler & John Durham Peters (1997). Ett fenomenologiskt perspektiv på livet och rummen med medier knyter ihop ramverket och utgår från Scannell (2014), Bakardjieva (2005) och Bengtsson (2007). Ämnet undersöks med en etnografiskt inspirerad metodologi i form av tre kvalitativa forskningsintervjuer med unga, musikintresserade och flitiga användare av Spotify. Det som framkom från intervjuerna var att en koncentrerad musikupplevelse är ovanlig, men inte omöjlig. När allt stämmer kan en djup och nära upplevelse nås. Användarna uttryckte i första hand andra kvalitéter hos det strömmade, det nya ”äkta” ansågs ligga i det personliga och kontrollerade flödet.

Följande studie undersöker vilka egenskaper konsumenter letar efter vid val av musikstreamingtjänst och huruvida det skiljer sig mellan konsumenter med musikalisk bakgrund och de utan musikalisk bakgrund. Studien undersöker musikkonsumentens nyttjande av musikstreamingtjänster, vilka egenskaper de värderar högst hos sina musikstreamingtjänster och vilka egenskaper de saknar. Studien har genom en kvantitativ metod, där en enkätundersökning har legat till grund för empiriinsamlingen, kommit fram till slutsatsen att musikkonsumenter letar efter ett stort och brett musikbibliotek, ett bra användargränssnitt, låg kostnad, exklusivt material, teknologiska funktioner, social interaktion och ljudkvalitet. Studien har även kommit till slutsatsen att lyssnarvanor skiljer sig mellan olika konsumenter, vi kan se att konsumenter med musikalisk bakgrund lyssnar mer frekvent och aktivt på musik. I uppsatsen används bland annat Lars Lilliestam teori om aktiv och passiv lyssning (Lilliestam, Lars, 2009, s. 93). Lars redogör för innebörden av aktiv lyssning, det är när man ger sin fulla koncentration och uppmärksamhet till musiken.

Spotify wants to explore the possibilities of social gaming within their desktop client. Thanks to their Spotify Apps API it is possible to build applications that integrate with the Spotify library while using modern web technologies. This thesis work consists of exploring what is possible using the Spotify App API and the most modern web technologies available. The main theme and goal of the Spotify App is to engage users in a social context. Creating a quiz application, which users can play along with using their smartphones, does this. This is targeted towards people being in the same room, sharing the experience. There is also a focus on usability and both group discussions and think-aloud interviews have been conducted regarding the development and design of the product.

This study focuses on the proactive methods against illegal downloading. This study will look into the new implemented IPRED law that could be seen as one attempt to prevent the illegal downloading. Furthermore, this study investigates how new services such as Spotify can be a legal alternative to the illegal downloading and also how the music industry has handled the transition from CD sales to the new digital media.   Our research consists of both qualitative and quantitative study where a survey has been conducted among 50 people in Jönköping University. The study also consists of two interviews from experts within the field which gave the study more credibility.   We discovered through our research that the music industry has been going through four different phases and that the actual state the music industry is that they have started to accept the technology and adjust their business to it. We have also discovered through our survey that the IPRED law has had an impact in the fight against illegal downloading. The winner is Spotify that most users have turned to when the IPRED law was introduced.

Mobile devices have evolved rapidly in recent years and increased usage and performance are pushing contemporary battery technology to its limits. The constrained battery resources mean that the importance of energy-efficient application design is growing and in this regard wireless network accesses are a major contributor to a mobile device's overall energy consumption. Additionally, the energy consumption characteristics of modern cellular technologies make small volumes of poorly scheduled traffic account for a substantial share of a device's total energy consumption. However, quantifying the communication energy footprint is cumbersome, making it difficult for developers to profile applications from an energy consumption perspective and optimize traffic patterns. This thesis examines the traffic patterns of the Android client of the popular multimedia streaming service Spotify with the intention to reduce its energy footprint, in terms of 3G energy consumption. The application's automated test environment is extended to capture network traffic, which is used to estimate energy consumption. Automated system tests are designed and executed on a physical Android device connected to a 3G network, shedding light on the traffic patterns of different application features. All traffic between the Spotify client application and the backend servers is encrypted. To extract information about the traffic, the application code is instrumented to output supplementary information to the Android system log. The system log is then used as a source of information to attribute data traffic to different application modules and specific lines of code. Two simple traffic shaping techniques, traffic aggregation and piggybacking, are implemented in the application to provide more energy-efficient traffic patterns. As a result, 3G energy consumption during normal music playback is reduced by 22-54%, and a more contrived scenario achieves a 60% reduction. The reductions are attained by rescheduling a small class of messages, most notably data tracking application usage. These messages were found to account for a small fraction of total traffic volume, but a large portion of the application's overall 3G energy consumption.

Currently, more and more people use music streaming websites to listen to music, and a music recommendation service is commonly provided on the music streaming websites. A good music recommender system improves people’s user experience of music streaming websites. Nevertheless, there are some issues regarding the existing music recommender systems that need to be looked into.The purpose of this thesis is to identify the weaknesses of music recommender systems. Spotify, a Swedish music streaming website, has a large number of users. As it is a widely known streaming service, it seems appropriate for a case study on the drawbacks of music recommender systems.The case study method has been chosen for doing this research. The process of making up this thesis was divided into three stages. At the first stage, some basic preparations for the thesis were done. The second stage was characterized by some empirical work, like interviews and questionnaires, to collect the required data. Those empirical findings were analyzed in the third part to help us to identify and define the drawbacks.The research results presented in this thesis contribute to close several knowledge gaps in the area of music recommender systems and could thus be beneficial to different actors: streaming website operators to identify drawbacks of their recommender system; designers of recommender systems to improve system design; and, last but not least, this thesis provides some useful advice to those who market music streaming websites.This thesis does not focus on the technical and algorithm fields, i.e. the hardware- and software-related background. Instead, the idea and the functions of the recommender system, its feedback loop and the user experience were subject to our research and discussion. The results of the thesis can provide those responsible with both and inspiration for creating more customized recommender systems.

Over the last years, the music industry has been disrupted by music streaming services which shifted the focus from owning music to accessing it. While the previous research focuses on the economic aspects, the social and cultural consequences remain largely unexplored. Existing research from an audience perspective is often focusing on one particular practice around music streaming and is mainly coming from and focusing on northern EU-countries. However, a broader contemplation of the sociocultural practices around music streaming is still missing. This thesis examines which sociocultural practices have emerged among urban and middle class Millennials in Germany when using the market-leading streaming provider Spotify and which affordances and gratifications these are based upon. The study is based on ten semi-structured interviews with German Millennials aged between 20 to 30 years. Three of these study participants are using a free Spotify account and seven the premium version. By conducting a thematic analysis against the theoretical background that interlinks practice theory, affordance theory and uses and gratifications theory, the practices are described and examined based on the underlying affordances and gratifications.The study found sociocultural practices around the themes social setting, listening mode, Spotify networks and music collection and outlines the underlying affordances and gratifications. During individual listening situations, users engage in the practices of mobile listening and mood management, while listening in social settings focused around navigating the group dynamics and the creation of context-sensitive playlists. The users also aim to create an unstructured and undisrupted music flow but are mainly listening in a passive manner while carrying out other activities. Due to social norms and privacy issues, the participants either reject the network function or build only small networks through which they were sharing and discovering music as well as creating playlists with friends. Lastly, users were building, organizing and maintaining individual music collections.

Under 2000-talet har de primära konsumtionskanalerna för musik gått från den traditionella radion och CD-skivan till Internet och dess tjänster så som Spotify och Deezer. Trots den nya tekniken och de nya möjligheterna så har både Spotify och Deezer implementerat en funktion som benämns som radio. Studien undersöker ur ett MDI-perspektiv vilken av musikstreamingtjänsterna Spotify och Deezer som har bäst användarupplevelse, när en användare aktivt vill upptäcka ny musik med hjälp av radiofunktionen. Detta undersöks med hjälp av en grupp studenter från KTH. Denna grupp besvarade en enkät om streamingvanor och deras relation till musik.  De utförde också ett “Think Aloud”-test under interaktion med radiofunktionerna. Deltagarna besvarade sedan en uppföljande enkät om vad de upplevt under testet. Både “Think Aloud”-testet och enkätstudien studerades utifrån hur användbar tjänsten var och hur musikrekommendationen presterade. På så sätt kunde vi se vilken tjänst som gav den bästa användarupplevelsen. Är användaren ute efter en musikupplevelse som främst spelar musik som användaren hört förut och troligtvis också uppskattar bör användaren använda sig av Spotifys radiofunktion som är mer träffsäker på att hitta låtar du gillar. Studien visar även att Spotifys radiofunktion kommer spela många låtar användaren redan hört. Vill användaren däremot aktivt hitta ny musik som användaren inte hört tidigare visar studiens resultat att Deezers radiofunktion är att föredra framför Spotifys radiofunktion. / In the 21st century the primary media consumption has evolved from traditional radio and CD listening to the Internet and software services like Spotify and Deezer. Despite the new technology, both Spotify and Deezer have implemented a so-called Radio function. This study investigates the music streaming services through a Human- Computer Interaction point of view. Furthermore it determines which one of the two has the better user experience when the user wants to discover new music with help from the Radio function. The studied group consists of 15 Engineering (Media technology) Students who answered a survey about streaming habits and their relation to music. Subsequently, they preformed a Think Aloud test during their interaction with the radio function. Following this, the participants answered a survey about their experiences during the test. Both the Think Aloud test and the surveys are observed through a usability point of view, by evaluating the usefulness of the services’ music recommendation. This way we could find which service had the best user experience. The radio function in Spotify provides music the users like in a higher rate than Deezer, however these songs are more likely to have been heard before by the user in comparison to Deezer. Therefore, if the user wants to actively find new music they like, Deezer’s radio function is preferable.

Spotify is a music streaming service that allows users to listen to their favourite music. Due to the rapid growth in the number of users, the amount of processing that must be provided by the company’s data centers is also growing. This growth in the data centers is necessary, despite the fact that much of the music content is actually sourced by other users based on a peer-to-peer model. Spotify’s backend (the infrastructure that Spotify operates to provide their music streaming service) consists of a number of different services, such as track search, storage, and others. As this infrastructure grows, some service may behave not as expected. Therefore it is important not only for Spotify’s operations (footnote: Also known as the Service Reliability Engineers Team (SRE)) team, but also for developers, to understand exactly how the various services are actually communicating. The problem is challenging because of the scale of the backend network and its rate of growth. In addition, the company aims to grow and expects to expand both the number of users and the amount of content that is available. A steadily increasing feature-set and support of additional platforms adds to the complexity. Another major challenge is to create tools which are useful to the operations team by providing information in a readily comprehensible way and hopefully integrating these tools into their daily routine. The ultimate goal is to design, develop, implement, and evaluate a tool which would help the operations team (and developers) to understand the behavior of the services that are deployed on Spotify’s backend network. The most critical information is to alert the operations staff when services are not operating as expected. Because different services are deployed on different servers the communication between these services is reflected in the network communication between these servers. In order to understand how the services are behaving when there are potentially many thousands of servers we will look for the patterns in the topology of this communication, rather than looking at the individual servers. This thesis describes the tools that successfully extract these patterns in the topology and compares them to the expected behavior. / Spotify är en växande musikströmningstjänst som möjliggör för dess användare att lyssna på sin favoritmusik. Med ett snabbt växande användartal, följer en tillväxt i kapacitet som måste tillhandahållas genom deras datacenter. Denna växande kapacitet är nödvändig trots det faktum att mycket av deras innehåll hämtas från andra användare via en peer-to-peer modell. Spotifys backend (den infrastruktur som kör Spotifys tjänster) består av ett antal distinkta typer som tillhandahåller bl.a. sökning och lagring. I takt med att deras backend växer, ökar risken att tjänster missköter sig. Därför är det inte bara viktigt för Spotifys driftgrupp, utan även för deras utvecklare, att förstå hur dessa kommunicerar. Detta problem är en utmaning p.g.a. deras storskaliga infrastruktur, och blir större i takt med att den växer. Företaget strävar efter tillväxt och förväntar detta i både antalet användare och tillgängligt innehåll. Stadigt ökande funktioner och antalet distinkta plattformar bidrar till komplexitet. Ytterligare en utmaning är att bidra med verktyg som kan användas av driftgrupp för att tillhandahålla information i ett tillgängligt och överskådligt format, och att förhoppningsvis integrera dessa i en daglig arbetsrutin. Det slutgiltiga målet är att designa, utveckla, implementera och utvärdera ett verktyg som låter deras driftgrupp (och utvecklare) förstå beteenden i olika tjänster som finns i Spotifys infrastruktur. Då dessa tjänster är utplacerade på olika servrar, reflekteras kommunikationen mellan dem i deras nätverketskommunikation. För att förstå tjänsternas beteende när det potentiellt kan finnas tusentals servrar bör vi leta efter mönster i topologin, istället för beteenden på individuella servrar.