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G Model POETIC 1239 No. of Pages 13 Table 2 Top 10 inter-cluster associations. Source Pop Hits Indie/Alternative Rock House/Lounge Soundtrack/Classical Rock 90s 00s Pop Stars/Latin Pop Country Female Rock Bands/Live Live Pop Relaxing Background Music M. Airoldi et al. / Poetics xxx (2015) xxx–xxx 11 Target Edge weight/N. videos source 94.2 49.3 45.0 24.7 20.4 17.1 9.5 9.1 7.4 6.9 Teen Pop Teen Pop Relaxing Relaxing Pop Hits Pop Hits Pop Hits Rock 90s Pop Hits Epic Music/Soundtrack Background Music Background Music (see also Lena & Peterson, 2008), we argue that the tightly connected groups of related music videos coming out of the computational analysis of the community structure of the network should be considered as rough miniatures of music categories as they emerge “from the ground-up” (Beer, 2013:153). Importantly, we note that conventional music genres still appear to be one of the major structuring forces in guiding listeners’ shared reception patterns on the platform. Interestingly, however, a kind of ‘situational’ or ‘functional’ consumption also emerges, whereby the listener sets apart purely stylistic or aesthetic conceptions of music genres to choose their soundtrack based on the effect it has on daily activities. Existing research regards this as typical of a ‘popular’ approach to music that is distant from the formal intellectual appreciation characterising ‘high art’ (see Frith, 1996; van Venrooij & Schmutz, 2010). “Functional” (or “umgangsmäbig”) genres such as dance, entertainment and liturgical music have been traditionally considered by musicologists as “trivial” or spurious, being just “one partial aspect of an event that is determined by extra-musical factors” (see Dahlhaus, 2004: 263). Nevertheless, we show how the reference to a ‘situational purpose of music reception’ characterises 7 out of 50 clusters, which feature music pieces tailored for relaxation, meditation, religious worship, and so on. Although this is not exactly a new trend in contemporary music markets see, for instance, electronic music producer Brian Eno’s “Music for Airports”, DeNora’s considerations about music and social situations DeNora (2000:11–14) and Fabbri’s reflections on background listening Fabbri (2003) – we expected it to be relatively marginal. Instead, it seems to be a quite relevant presence if we consider that more than 10% of YouTube music in our sample follows this logic. It is also worth mentioning that a similar ‘situational’ form of categorisation is observed on other online sources of digital music such as the streaming service Spotify, where ready-made playlists are often characterised by comparable ‘situational’ frames. The acknowledgment of such an emerging trend in current digital music reception seems to be particularly important if we think about the subcultural meaning of music that historically plays a key role in the formation of youth identity and peer recognition in adolescence (Hall & Jefferson, 1976). Both the analyses of the clusters’ content and of the resulting network of clustered associations confirm that ‘relatedness’ on YouTube is generally synonymous of ‘stylistic contiguity’. Our results may sound obvious at a superficial glance: being a commercial service provider, YouTube is naturally interested in giving meaningful suggestions to its users (Celma, 2010). Still, if it is true that the musical field “together with its internal relationships, is never still it is always in movement” (Middleton, 1990: 7), then it could be argued that studies like this offer room for tracking its transformations in an inductive way (see also Beer, 2013; Savage & Gayo, 2011; van Venrooij, 2009). We acknowledge that our analysis has some limitations, particularly in relation to the fact that our 22,141 videos are not a statistically representative sample of the music content uploaded on YouTube. Yet, it must also be recognised that this would have been a major concern if the goal had been to provide inferences on the composition of the overall repository of YouTube videos related to music, or to perform quantitative comparisons. Instead, for the purposes of the present work, the snowball sampling is coherent with the main aim of the analysis; that is, doing an exploratory study into the logic of association among videos. We hope that future studies may build on our work, and pursue this more ambitious line of inquiry. With regards to the nature of our findings, it must also be acknowledged that some of the clusters are not entirely composed of musical contents (‘Pop Stars Interview’, ‘Metal/Rock Live/Documentary’, ‘Guitar Tutorial/For Musicians’, ‘Flute/Piano Cover/Tutorial’), while others are aesthetically heterogeneous (‘Soul/Singers/Orchestra’, ‘Latin/World Music/Meditation’). More generally speaking, the logic of the recommendation algorithm, primarily based on mass listening behaviour, implies the risk of observing “different cultures of categorization [ . . . ] removed from their social basis” (Holt, 2007: 29). Nevertheless, this article provides further empirical support to the argument that digital platforms offer new epistemological and methodological tools to cultural sociology to investigate social patterns by inductively exploring users’ practices and imaginaries (see Beer, 2013). More particularly with regards to the sociological study of music, we believe that a network-based approach that is capable of grasping the relational nature of music’s semantic space is probably what is now most useful for the study of genres (as other empirical research has also shown, e.g. Crossley, 2008; van Venrooij, 2009). Following those contributions that approach music classification in an eminently sociological way, our methodological perspective, if replicated on a larger scale, can arguably shed light on the ‘folk categories’ used by contemporary digital music Please cite this article in press as: M. Airoldi, et al., Follow the algorithm: An exploratory investigation of music on YouTube, Poetics (2016), http://dx.doi.org/10.1016/j.poetic.2016.05.001PDF Image | Follow the algorithm: An exploratory investigation of music on YouTube
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