And the final speaker in this Social Media & Society 2024 panel is Steven Gamble, who begins by pointing the appropriation of Black American culture in contemporary music; his focus is especially on Ariana Grande as a multiply constructed pop persona who presents a racial ambiguity.

This racially ambiguous representation has been described as ‘blackfishing’, and there is considerable discussion online from both fans and detractors about her race and ethnicity, running even to long post that pretend to forensically retrace her ethnic heritage. Such discussions tend to combine a variety of perspectives on blackfishing in general, on Ariana Grande …

The second speaker in this Social Media & Society 2024 panel is Ed Katrak Spencer, whose focus is on the clickbait conspiracism surrounding Britney Spears. There is a continuous refuelling of speculative Spears discourse: music-related online controversy is a continuous rhythm rather than singular event, and online conspiracism is itself becoming a quasi-musical vibe.

Even after the end of Spears’s 13-year conservatorship, several prominent social media users refused to let go of the #FreeBritney conspiracy theory; there are even theories that the real Spears has been replaced by a body double or by AI. But Spears has always been described …

For the final Social Media & Society 2024 session today I’m in a panel on online music cultures, which starts with Jenessa Williams, whose interest is in how fans decide to continue or discontinue their fandom for artists accused of sexual misconduct, especially also in the context of changing music consumption habits. The focus here is on smaller, genre-specific cases rather than widely publicised allegations against superstars.

This identified three main modes of reaction, involving cancellation, confliction, and anti-cancellation: cancellation involved feminist-coded rage, disappointment, and betrayal, and was expressed in strong and absolutist phrasing and explicit actions of condemnation (binning …

The final speaker in this AoIR 2019 session is Arnt Maasø, who shifts our attention to the role of metrics in the music business. Datafication has grown in the music industry as well, with a strong turn to metrics in recent years. Where some decades ago the industry was run by self-taught entrepreneurs who were running their businesses predominantly by gut instinct, now music metrics are everywhere and directly influence decision-making.

Arnt’s project conducted surveys and interviews with professionals in the Norwegian music industry. Almost half of the survey respondents use music metrics in their jobs, but such use is …

The final presenters in this AoIR 2016 session are my colleagues Peta Mitchell and Felix Münch, who also focus on the Twitter reaction to David Bowie's death. Twitter as a platform can be useful for studying public responses to such events, but at the same time the focus on a hashtag only also limits the study to deliberately self-selecting tweets and users; a focus on 'Bowie' as a keyword provides a different perspective. This is also complicated by the one percent rate limit of the Twitter API, as 'Bowie' tweets spiked well above that limit.

Most of the millions of …

The next paper in this AoIR 2016 session is by Hilde van den Bulck, which shifts our focus to the mourning of David Bowie after his death on 10 January 2016. Bowie had had a stellar and constantly shifting career, of course, but had also managed to keep his private life comparatively private, which is why his death came quite unexpectedly. Not least because of this there was a massive reaction to news of his death on Facebook and Twitter.

One of the spaces that quickly emerged for such 'i-mourning' was the #bowie hashtag on Twitter. This became …

The next Web Science 2016 presenter is Jack Webster, who focusses on music recommender systems. Such recommender systems could generate filter bubbles, but that threat is nothing new; the cultural intermediaries described by Pierre Bourdieu fulfilled very similar roles and could have engendered very similar patterns.

But music recommender systems do not draw on a lifetime of personal experience, but rather utilise large datasets on users' engagement with music streaming and download services, applying algorithms designed by human coders. How do these different human and technological actors come together in creating and operating recommender systems, then?

Cultural intermediaries are the …