Music Web Radio Marjorie Kibby Is a Senior Lecturer in Communication and Culture at the University of Newcastle, Australia

Australian Journal of Emerging Technologies and Society Vol. 4, No. 2, 2006, pp: 81-93 Radio That Listens to Me: Y!Music Web Radio Marjorie Kibby is a Senior Lecturer in Communication and Culture at the University of Newcastle, Australia. Her research interests include popular music, the culture of the Internet, and intersections of the two. Her recent publications include articles on online music communities, internet folklore and music file collections.

Abstract A study of listening to Y!Music revealed the extent to which it was an interactive experience. The auto-ethnography was conducted as a capture of the music stream and a journal of interactions with the station. The music that was played was then analysed to determine the effect of judgements on the selections. The listening state was identified through involvement in the optional activities provided: accessing additional information, shopping for music and music related products, and communicating with other fans. The study revealed that the music-rating algorithm used by Y!Music is complex and it takes time to work out the implications of particular interactions. Y!Music may have been listening to me, but it took time and energy to make our communications effective. This effort, combined with the range of activities that accompanied listening, meant that web radio was a more engaging experience than the usual experience of broadcast radio. Keywords: Web radio; streaming audio; Y!Music; online music; interactivity; autoethnography.

©Australian Journal of Emerging Technologies and Society 2006 ISSN 1449 - 0706 http://www.swin.edu.au/ajets

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Introduction While there has been a considerable amount of research and discussion on streaming audio, most of it has come from departments of computer science, marketing and law (see Li et al 2005), as various interest groups come to terms with how music distribution over the web will dramatically change how the music industry operates. Much less research has had as its focus how online radio stations affect the listening experience of music consumers. Given that listening to music online may be an interactive multi-media experience, it is possible that the effect will be significant. Y!Music is part of the Yahoo Music service, which provides access to a range of music products, information and services including news, reviews, downloads and charts, in a variety of media formats. It also provides a large range of pre-programmed radio stations classified by genre and theme, and a facility called ‘My Station’ which allows the listener to determine the songs that will be streamed. A considerable level of interactivity and personalization would make listening to Y!Music a significantly different experience from listening to broadcast radio. An auto-ethnographic study of Y!Music reveals that Y!Music did give me, as a listener, a feeling of control over the playlist of the station, and an engaged experience that was quite different from the background role the radio usually plays in my life. However, a reflection on the mechanisms of choice over the Y!Music playlist reveals that the control by the listener is limited.

Methodology This case study of the interactivity of Y!Music Radio was undertaken as an autoethnography. Ethnographic research has an extensive history beginning in anthropology and travelling across the social sciences to fields such as geography and internet studies. Through this history, ethnography has evolved from the Victorian interest in documenting exotic cultures in distant countries, to a contemporary qualitative methodology that explores the researcher’s own culture, acknowledging multiple knowledges and viewpoints. Auto- ethnography goes one step beyond participant / observer studies to position the researcher as the researched, and it is generally understood as “the process by which the researcher chooses to make explicit use of [their] own positionality, involvements and experiences as an integral part of ethnographic research” (Cloke, Crang & Goodwin 1999: 333). The method is particularly evident in research into disability and pain (Neville 2004), professional practice (Nicotera 1999), and post-colonial studies (Erikson 2003). It is also beginning to be used as a research method in the study of information technology and its applications (Cunningham & Jones 2005; Duncan 2004). An ethnographic study of a group of people who listened to Y!Music Radio would have major disadvantages. Firstly, it would rely on people having “the cognitive awareness to describe the nuances of their responses” to online music (Duncan 2004: 2) and the language necessary to describe those responses; or for a researcher to gain permission for the observation of participants listening to music, a personal and emotional practice. Secondly, it would be time-intensive, which is a distinct disadvantage when researching the use of software or internet applications which can change significantly and rapidly. Thirdly, in the absence of research literature on listeners’ interactions with web radio, ethnography would require initial research to establish guidelines for framing research questions, collecting data and applying analytical tools.

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An auto-ethnography overcomes some of these problems in that the researcher as subject has the necessary scholarship to identify significant responses and to record them appropriately; the researcher’s immersion in the area under study allows the research to be compressed into a brief timeframe without extensive intrusion into the lives of volunteers; and where the researcher is the researched there is a degree of flexibility available in the design and implementation of the research project. Auto-ethnography as a research method is not without its critics (see, for example, Denzin & Lincoln 1994; Sparkes 2000). Amongst the criticisms made, are that auto-ethnography is too self-indulgent and narcissistic (Coffey 1999) and is not able to be assessed by traditional criteria used to judge qualitative inquiries (Sparkes 2000). Duncan, however, counters that the quality of auto-ethnographic studies can be judged by the same criteria of legitimacy and representation that any research must address; criteria “related to study boundaries, instrumental utility, construct validity, external validity, reliability, and scholarship” (Duncan 2004: 8).

Y!Music Webcasting, or online radio, is rapidly becoming a preferred alternative to terrestrial radio stations. “Online radio allows listeners to swap local radio fare for more exotic programming, turning everyday PCs into world receivers, and offers a large variety of special interest Webcasts catering to very genre-specific tastes” (Bruns 2003: 1). With thousands of webcasters across the world offering hundreds of channels each, web radio listeners have the benefit of an abundance of content, but also the task of locating those stations that mesh with their taste or mood. In response, Yahoo launched an online music service that allows users to customise a station of their own based on a system of rating their favourite genres, artists and songs. Originally known as LaunchCast, Y!Music is now just one of many similar services. However Y!Music does seem to be more interactive than its competitors, offering a greater degree of control while requiring a little more work to set up. While other personalised webcasts draw on lists of favourite artists or playlogs of your MP3 software, with Y!Music tracks are rated either in the database or as they play, and the station plays proportionally more or less of that type of music and additional similar music that has not been rated. Y!Music’s slogan ‘Radio that listens to you’ emphasises this interactive element. Y!Music is available in free versions worldwide, and a premium fee-based service in the United States and Canada and to British Telecom (BT) Yahoo! Internet customers in the United Kingdom. Y!Music also provides a large and growing number of pre-set stations, divided into Genre Stations and Theme Stations, as well as fan stations that play music from particular artists and others with a similar style, and television spin-off stations such as Dancing with the Stars and Desperate Housewives. The personalised stations of other users can also be listened to. Positively rating any of the music on these stations adds it to the playlist of the personal station. In an increasing convergence of media forms, while listening to Y!Music, information, news, photos, videos, interviews, discographies, websites, albums for purchase and tracks to download are all available at a mouse-click. Communicating with other users is also possible using Yahoo Instant Messaging or Yahoo Groups, and a one click ‘Share this Station’ feature allows a user to tell others about their personal station. The LaunchCast user group on Yahoo Groups enables an exchange of experiences and opinions between users and product managers and developers.

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Getting started with ‘My Station’ was fairly uncomplicated; I had a Yahoo ID and a popular computer setup. Y!Music does not have a stand-alone desktop player, instead relying on Internet Explorer or the player built into Yahoo Messenger’s instant messaging application. There were some general set-up tasks such as choosing whether to rate out of five stars or one hundred points but, once signed in, the first step was to indicate some broad music preferences by rating genres, Y!Music’s first level of music selection.

Genre As with the layout of stock in record stores, the divisions in music catalogues and the organisation of music charts and music awards, Y!Music’s emphasis on genre suggests that popular music can be categorised into genres whose boundaries and identifying features are concrete and easily understood. However, ‘classes of music do not always have distinct boundaries’ (McKinney & Breebaart 2003: 7). There are general characteristics that can be used to classify music into categories – stylistic traits such as conventions of composition, instrumentation and performance – however many other non-acoustic properties contribute to the labelling of a piece of music as belonging to a particular genre, including the artist, record label, visual style and audience interaction. The multiple possible interpretations of these characteristics suggest that genre divisions are, at best, highly fluid. It is not difficult to find examples of how genre distinctions become meaningless in practice. Peterson (1997: 2) gives the example of three ‘country’ artists: Hank Williams, Jr., Vince Gill, and k.d. lang. As Peterson says: Persons who choose any one of these are very unlikely to like the other two. Those who choose Hank Williams, Jr. are likely to also like Steve Earle and Nine Inch Nails; those who choose Vince Gill are likely to add Mary Chapin Carpenter and the likes of Aaron Neville as well as romantic pop singers; those who choose k.d. lang are likely to select other feminist and lesbian artists who have never flirted with country music (Peterson 1997: 2). But regardless of how meaningless music categories become, developments in digital technologies that enable users to enjoy vast amounts of music require a mechanism to sort, filter, process, store and retrieve audio content: The new context of Electronic Music Distribution and systematic exploitation of large musical databases creates a need to produce symbolic descriptions of music titles. Musical genre is probably the most obvious descriptor … and it is probably the most widely used (Aucouturier & Pachet 2003: 83). So at just the historical moment when musicians and fans are breaking down genre boundaries in practice, those boundaries are being virtually carved in stone in audio databases. While musical genre is widely used to classify and describe music titles, there is little commonality across classifications from different sources. A comparison of allmusic.com (531 genres), amazon.com (719 genres) and mp3.com (430 genres) shows only 70 words common to the three taxonomies (Pachet & Cazaly 2000), and a wide variation in how subgenres are identified and described. More importantly, the same study shows that there is no shared structure among the similar taxons, with even common terms such as ‘rock’ and ‘pop’ being used to denote quite different sets of songs. Currently the primary approach to music genre classification is a manual system that uses expert human knowledge about music titles. This is best able to deal with ‘illogical’

84 Kibby: Radio That Listens to Me: Y!Music Web Radio taxonomies where music may be classified by era (eighties rock), source (world music), artist style (crooner) or lyrical content (love songs). Most of the systems that extract genre information automatically model these genre classifications, filtering tracks on the basis of features including timbrel texture, rhythmic content and pitch content, which have been identified in key samples of the genre. While the extraction of acoustic features from music files has a long history, “it has so far proved extremely difficult to determine how to use such features to represent high-level semantic concepts” (Shen, Shepherd & Ngu 2005: 253) such as current music genre and subgenre descriptors. Research is continuing into the development of a new genre taxonomy, where the descriptors would be objective, independent of other descriptors in the database, similar in form, and semantically consistent and able to support emerging genres (Pachet & Cazaly 2000). To date none of the automatic systems have been able to effectively duplicate human perceptions of music characteristics and categories. In recent years we have seen the rise of user-developed categorisation, using organic systems based on ‘tags’ or user-defined labels which can be attached to information and products without the constraints of hierarchical categories. The social book-marking service del.icio.us, is an example of the use of ‘folksonomy’ where labels are attached in use, by users. However Yahoo in attempting to bring order to the Web, decided on an ontologically managed list and has used a similar taxonomy in organising its music service. In accordance with the advice given by Launchcast Help to set up ‘My Station’ on Y!Music, I first selected the genres I wanted to hear, rating each in line with how much of that particular genre I wished to hear: Country 100, Blues 90, Rock 80, Folk 70. Some genres were left unrated, and several were marked ‘never play’. Within each of the four rated genres, I then rated sub-genres, leaving some unrated again, and marking some ‘never play’. This was not as straightforward as I expected. Some categories such as ‘Cowboy’ I was not familiar with, but there was no description or list or artists on the ‘edit genres’ page. Other genres such as Folk-Pop I had a perception of that wasn’t matched by the artists under that label – while I envisioned contemporary commercial folk music, Y!Music listed popular artists from the fifties and sixties. There was a description on the pre-programmed station page of the various sub-genres that had a programmed station, but these categories were quite different from those from which I was invited to select music for my station, with only Classic Country common to both lists. Given the importance of an understanding of genre labels to setting up a personal station that truly reflected my tastes, Y!Music provided little assistance in this area. There was an assumption that the varied and changing labels were transparent. The sub-genre Alt-Country, was given its alternative name Americana in the list of stations. The description of the Americana station is: “Americana aka Alt-Country aka Neo-traditional aka Insurgent Country aka Roots Revival aka Cosmic American Music. Call it what you want, this genre’s popularity has been growing since the early 90s” (Y!Music Radio 2006). Goodman (1999) defines alternative country music as music that draws on traditional country music styles, themes and images while incorporating a variety of modern musical and non- musical influences. Its origins can be traced back to artists who retained a country authenticity while adopting rock rhythms and instruments as a conscious opposition to the mass-produced country pop exemplified by Garth Brooks. Artists such as Willie Nelson, Kris Kristofferson and Johnny Cash labelled themselves ‘outlaws’. At around the same time, musicians who spent their teens in punk bands matured musically into a ‘joining of grinding punk, country rock and acoustic country; a focus on the darker side of small town life; and a heightened social/political consciousness’ (Goodman 1999: 309). Bands like Uncle Tupelo,

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Jason and the Scorchers, John Doe, and Freakwater, connected the personal protest of punk and grunge with the everyday narratives of traditional country. Peterson and Beal suggest that rather than being a single style of music: “alternative country is more a congeries of music that fans find sounds well together and express much the same sentiments” (2001: 238), such as nostalgia, alienation, working-class identity, and anti- capitalist protest. Certainly no distinct musical features bind the genre, and if experienced fans can argue that Iron and Wine is alt.country but Wilco is not (or vice versa) then the category presents a serious challenge for the music file classification systems of Y!Music. Once the station is set up, users can add mood filters, by selecting a sub-set of genres that correspond to a particular mood. This assumes that all songs within a particular genre reflect a similar mood. I could, I suppose, set up At Work with Show Tunes and Easy Listening, but Y!Music does not allow refinements like a station Love Gone Wrong with a subset of melancholy Blues, Folk and Country tracks. In addition Show Tunes and Easy Listening would be added to my everyday station and any rating made to my mood-filtered station would affect the playlist of ‘My Station’ as a whole. There is only one set of ratings which applies to both my main station and any mood stations I establish; which for me seemed to remove the usefulness of mood filtering. The Y!Music pre-programmed stations include a number of mood-based categories, such as T.G.I.F., Spring Break, Meditation, and Chill Out, with playlists that cross genre boundaries. These will probably be more useful than trying to set up personal genre-based mood stations that are distinct from, but closely linked to my main station. Mood management, alongside the maintenance of self-identity and the management of interpersonal relationships, is one of the principal functions of music in everyday life (Hargreaves & North 1999: 85). Music can act as a vehicle to express emotions which cannot otherwise be conveyed; it can reflect, support and intensify moods; and it can bring about an alteration in emotional states. Creating a program of music selections designed to create or maintain a specific mood is not new: Muzak’s growth was fuelled by psychologists’ studies showing that particular types of sounds could affect productivity, spending patterns, or tolerance of inconveniences (Klahr 2002). Automatic music classification systems and MP3 tools like Moodlogic and Cantametrix are allowing users to create their own Muzak. Songs can be selected, not only on the basis of broad genres, but also by features such as style, weight and tempo, and characteristics like upbeat, aggressive or mellow. It seems that just two music dimensions explain the transfer of emotion from performer to listener ─ tempo and articulation – where tempo ranges from fast to slow, and articulation varies from staccato to legato (Juslin 2000). From this starting point comes the assumption that a mathematical algorithm can capture the essence of a piece of music and deliver a track that matches the emotional state of the listener (Feng, Zhuang & Pan 2003). Given the major role that music plays in emotional self-management: “from ‘revving up’ to ‘calming down’ to ‘venting’ strong emotions, to producing mental concentration” (DeNora 1999: 34), and the affective investment that listeners have in particular genres, there is little research into mood and genre other than that linking anger and heavy metal. Subdividing my genre-based Y!Music station into intersecting sets of mood-based categories will have to wait for the development of more refined taxonomies and more sophisticated algorithms.

Artists and Albums As I had only a modest degree of faith in the genre selections to deliver the music that I wanted to hear, I then rated a number of artists in the database. I enjoyed this; it was like a ‘seven degrees of separation’ game. Rating Steve Earle at 100/100 brought up a list of

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‘similar’ artists: Tammy Wynette, George Jones, Wilco, Johnny Cash, Darryl Worley, Dwight Yoakam, Paul Butterfield, Joe Nichols, Willie Dixon, Terri Clark, Montgomery Gentry, Blake Shelton, John Mayall, Dierka Bently, Howlin’ Wolf, John Michael Montgomery, Robert Cray, Albert King. Many of these I knew well and rated, some I clicked to get more information, and was led to a new listing of ‘similar’ artists. If I did not know the music, I left the artist unrated. Three names came up that I did not want included, so I rated them ‘never play’ ─ R.E.M, The Beatles and Red Sovine. After about three hours I had one hundred artists rated. Emmylou Harris, Steve Earle, Johnny Cash, John Prine, James McMurtry, Social Distortion and Iron and Wine were rated 100/100 so for these artists I moved on to rate albums. This step brought me back to earth a little. It was one thing to ask Y!Music to play lots of a particular artist, and another to then discover that they had very few of his albums from which to choose tracks for this high rotation. The Australian version of Y!Music seemed to select tracks primarily from compilation albums such as Best Of the Blues and Johnny Cash’s Greatest Hits. Ratings are about play frequency, not a judgement of excellence, so those albums I currently want to hear regularly I rated highly, some favourites I gave an average rating to if I thought that they might pall if overplayed. Where an artist had only one or two albums available, I lowered the artist rating. I then rated highly a few new albums that I had seen positively reviewed, thinking that on hearing tracks from them I could rate the individual songs, get a feel for the album and make a purchasing decision, and re-rate the album.

Webcasting and Royalties Y!Music encourages users to rate with a set of ratings levels, from ‘Newbie’ with less than 100 ratings to ‘Ratings Master’ with over 10,000 ratings, and a rolling tally showing how many more ratings I need to get to the next level. While it would seem that the more music I rate, the more information Y!Music has to create a playlist tailored to my preferences, licensing requirements demand that a proportion of what is played is unrated. So if I rate everything that I could potentially like even a little, Y!Music will have to play music I patently do not like in order to fill the quota of un-rated tracks. Bruns (2003) outlines the hardline approach that the Recording Industry Association of America and its royalty collection agency have taken with new media services, leading to the crippling of Napster and the dominance of less user-friendly industry-run services. Yahoo was instrumental in negotiating a pricing structure with the RIAA that was designed to keep small webcasters very small, and encourage mid-size webcast operators into larger networks and bigger media organisations. Recently Yahoo have been forced to prove that it has not been in breach of its licensing requirements in providing music ‘on-demand’ via Y!Music (The Online Music Report 2005). The help pages remind users: “Launchcast is not a personal jukebox, it’s radio.” Around half of the songs played will be unrated.

‘My Station’ It took me around three hours to set up ‘My Station’, including time taken to explore the various extras such as photos and videoclips, and to listen to selections from related artists that were suggested to me. Following the discussion on Launchcast Group, it would seem that very few people would do this in a single block of time. Most people posting recommendations on setting up stations suggest rating favourite genres highly, leaving everything else unrated and then rating tracks, albums and musicians as the station plays. I listened to ‘My Station’ for an hour and fifteen minutes. In this time Y!Music played nine songs from artists that I had rated, and ten songs that were unrated. Of the unrated songs, five were played because ‘This song is popular in the genre of your station’, and five because

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‘This song matches your genre preferences’. After seventy-five minutes, I received a pop-up message asking if I was still there so I used that as an end to the session. For the first ten sessions I did no further ratings, but listened to the station as I had set it up. The first ten sessions amounted to nearly eleven-and-a-half hours of playing time. During these sessions ninety-four rated and eighty-six unrated songs were played. Forty-nine of the rated songs were from my top seven artists (Emmylou Harris, Steve Earle, Johnny Cash, John Prine, James McMurtry, Social Distortion and Iron and Wine) with a further ten songs played because they were recommended by fans of these favourite artists. Forty-four songs were played because they matched my genre preferences and twenty-nine because they were popular in the genre of my station. There were eighteen songs from artists I had never heard of: five Chris Cagle tracks, six Trick Pony tracks and one each from Andy Griggs, Montgomery Gentry, Wayne Hancock, Jesse Alexander, Collin Raye, Shelly Fairchild and Blaine Larsen. There were some pleasant surprises: Flaco Jimanez, Buzzcocks, Ry Cooder. And a favourite, Townes van Zandt, whom I had forgotten to rate, came up under ‘Recommended for you’ as did Dire Straight’s Sultan’s of Swing. Overall I was fairly pleased with ‘My Station’, though it was perhaps a little biased towards country rather than alt.country. Other than Ann Murray’s Spanish version of Broken Hearted Me there were no tracks that I was moved to skip. The unrated songs were often a little too country, particularly those described as being artists recommended by the fans of Johnny Cash, so I down-rated Johnny Cash from 100 to 70. I was also hearing too much of Chris Cagle and Trick Pony, so I rated these ‘never play’ to force new selections. Over the next sessions I followed the same pattern, giving a low rating to unrated artists who were played too frequently, rating songs that I liked and leaving unrated any songs or artists that I was ambivalent about. As I rated more songs I noticed that Y!Music was giving ‘You rated this song’ as a reason for playing more often than ‘You rated this artist’. The song rating seemed to take preference over artist and album ratings. In general, rated songs were played more often at the beginning of a session, and unrated songs began to play after I had been listening for a while. Chris Cagle and Trick Pony were not played after I rated them ‘never play’, and Sara Evans, Little Texas, and Charly McClain became the most played unrated artists. On the whole, the music played was predominantly alt.country, with some country, and a little blues, classic rock and old-school punk mixed in. Occasionally I re-rated artists to reduce the number of classic country tracks played. Rated music accounted for 58% of the music played. Music derived from my genre preferences made up 34% of the music played. Twenty-five percent of the tracks played came from artists that I had rated at 90 or above. At the end of thirty hours I had rated artists (107) albums (186) and songs (296) and Yahoo gave me the label of ‘Trendsetter’, telling me that I needed 411 more ratings to become a ‘Fanatic.’ Overall I was pleased with the music that was being played, the sound was fairly consistent and there was a nice mix of old favourites and new surprises. Not everyone, though, is as content with their station as I was: I have tried my best to rate albums and artists 4 stars, but the computer doesn't give me any recommendations based on music that I like. When I look at my recommendations in the yahoo music engine, they seem as if they are being picked at random. Nothing related to my 4 star albums and artists is there. Posted to Launchcast Groups 27/04/06 I am a long time user, and really enjoy the variety, but am very upset every time a song comes on that is ‘Recommended by Yahoo’ because it is NEVER in a genre that is anywhere close to the type of music that I like. Every time one of these

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recommendations plays, I do 4 things - mute the audio until the tune is loaded when I then click to go to a new tune, click on artist name, then rate artist at zero, then select all similar artists and zero them as well. But Launch is still managing to find artists I have not zeroed - it must have found about 8-10 just this morning. Posted to Launchcast Groups 04/04/06 I made a new station this morning and i X'd out all of the genres that i didn't want except for the rock ones that i did obviously my point being is that i thought that when a recommendation was made say this artist was recommended by fans of megadeth or whatever the thing says it was only supposed to recommend artists within the genre's that you have rated? because altho i have rated one or two artists that fall outside of my rock categories i am now getting artists recommended to me that don't fit my categories at all. Posted to Launchcast Groups 09/01/06 Todd Beaupre who is Director, Personalization, for Yahoo! Music usually explains in the Launchcast discussion group why individuals are receiving the music that they complain about. Generally it is because they have rated too many tracks and Y!Music has to go outside their chosen genres to find unrated tracks, or they have rated very highly an artist that is outside their usual genre preferences so other artists from that genre are played, or there is insufficient distribution of ratings with few points between most preferred and least preferred, so less favored artists are given equal rotation.

Interactivity and Flow Broadcast music radio seems to support the premise that ‘no one cares whether you listen to the radio so long as you do not turn it off’ (Berland 1990: 179). Music programming follows a formula designed to accompany listeners as they go about everyday activities. ‘Its primary goal is to accompany us through breakfast, work and travel without stimulating either too much attention or any thought of turning it off’ (Berland 1990: 179). Its purpose is to provide a background to our lives, like wallpaper that goes unnoticed for the most part, while its details are absorbed into our subconscious minds. Music radio programming is based on the assumption that radio listeners are in fact not listening, or at least not listening very closely. Listening to Y!Music can be a much more engaged, interactive experience. While Y!Music can just play in the background, the listener is encouraged to engage in a level of interaction. As well as invitations to rate the song, album and artist, the listener also receives suggestions to compare prices for the album on Yahoo shopping; to buy items related to the artist on eBay; to browse the stations of members who like the song, the album or the artist; and to view a list of all of the recently played songs. There are also links to news, artist spotlights, music reviews, gig guides, and singles and albums charts. In addition, there are invitations to play Yahoo games and to flirt on Yahoo personals as you listen. Interactivity in online sites is generally seen as ‘an inherently good thing’ (Liu 2002: 53) that would change the way that we shop, play and learn. While there are different ways of defining interactivity, Steuer (1992: 84) suggests that interactivity is ‘the extent to which users can participate in modifying the format and content of a mediated environment in real time.’ Liu (2002: 54) specifies three dimensions of interactivity: active control, where the user can undertake voluntary and instrumental actions which have a noticeable effect on their experience; two-way communication where they can both transmit messages to site managers and other users, and receive messages from them; and synchronicity, where the effect of the user input is apparent almost simultaneously with that input. A comparison of interactive and non-interactive web sites showed that interactive elements on a web site

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‘leads to more information processing, higher favorability towards the product and the Web site, and greater flow state intensity’ (Sicilia, Ruiz & Munuera 2005: 31). Csikszentmihalyi (1975: 36) introduced the concept of ‘flow’ to refer to ‘the holistic experience that people feel when they act with total involvement’ and a number of researchers have used the term to describe users’ involvement in online activities (see Ha & Chan-Olmsted 2001; Novak, Hoffman & Yung 2000). The strength of the experience of flow is a function of the extent to which the user is involved in the mediated environment rather than in the immediate physical environment. Interactive elements in the online environment can facilitate the occurrence of flow; as the levels of control, concentration, comfort with acquired skills, and knowledge of what needs to be done all contribute to the sense of total involvement. While simply listening to music can be an all-encompassing experience, this is different from the flow state, in that the listener lacks a sense of achievement or of an active contribution to the result. The interactive nature of Y!Music did lead to a flow state where I was fully involved in ‘My Station’. I found it difficult to listen while I was engaged in any other activity; it became a totally involving activity itself, or rather all encompassing convergent activities. For some listeners this would be a disadvantage, and from postings to Launchcast Groups it is evident that for a considerable number of Y!Music listeners this is not their goal, and the extra effort needed to manage the control over their station did not pay off in providing a seamless background to external activities.

Y!Music Listens to Me While I did feel that Y!Music listens to me, it was not without significant effort on my part to facilitate the communication. I felt that Y!Music and I had quite different conceptual maps, particularly where genre classifications were concerned, and getting the music I wanted meant second guessing what it was that Y!Music thought I was ‘saying’ to it, and adjusting my vocabulary accordingly. This communication gap stemmed in part from the organisation and classification of music tracks. My experience was reminiscent of Will Straw’s (1997) music consumers, who stumbled lost and confused amongst the shelves and racks of the music superstore, unable to correlate their convergent musical tastes with the rigid taxonomies on the signs and labels. Yahoo was one of the first services to attempt to bring order to the Web, and to do so they established a directory with hierarchies, categories and subcategories. Faced with the possibility of organising information without any physical constraints, they built virtual shelves and put up racks adding labels and signs to re-direct browsers who didn’t understand the taxonomy. Straw’s confused consumers were offered not a seamless environment where they could browse for the sites that meshed with their needs, but a rigid system within which they could search for specifically labelled items. Y!Music uses the same system. If I want to listen to music that I think of as arty post-punk I have to find my way to the Independent Rock section, and the Modern Folk section, and the New Wave Pop section. Y!Music’s taxonomy is based on employing categorisers to guess where people might look for a particular artist, album or track. The social tagging systems used by del.icio.us, Flickr and CiteULike use ‘folksonomies’ to give every item a unique identifier. If Y!Music used a folksonomy there would be no need for shelves and racks, as I could tag every track that I thought was ‘arty post-punk’ with that label, and call up all tracks that others identified similarly. Unique identifiers allow for the fact that not every track by an individual artist has the same sound or mood, and that genres such as Country contain individual songs that will

90 Kibby: Radio That Listens to Me: Y!Music Web Radio be hated and others that will be loved by the same listener. The major advantage of using a folksonomy to organise Y!Music would be that there would be no disjuncture between the conceptual map of the user and the identifiers attached to the tracks. The words of the users would be the words on the site, as the descriptors used in sub-cultural groups, performance spaces, and the street press, became the official classification terms. As new words appear to describe emerging musical trends they would be attached to new tracks and old numbers by the listeners themselves. Research efforts continue to design a new taxonomy of musical genres that has objectivity, independency, similarity, consistency and evolutivity (Pachet & Cazaly, 2000), but Tom Coates “who thinks up neat stuff for Yahoo” (Coates 2005) sees tags as a way of helping people explore a musical space by making it possible for them to move between songs, artists, albums, radio shows and back to other songs, as tags make use of individuals’ classification systems to reach consensus on musical descriptors. While Y!Music imposes a classification system upon me, and compels me to choose between the categories it has defined, there are limits to the freedom I have to design my own radio station. Y!Music may listen to me, but only if I choose my words carefully.

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