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During times of crisis such as the Covid-19 pandemic, digital platforms are under public scrutiny to guarantee users’ online safety and wellbeing. Following inconsistencies in how platforms moderate online content and behavior, governments around the world are putting pressure on them to curb the spread of illegal and lawful harmful content and behavior (e.g., UK’s Draft Online Safety Bill). These efforts, though, mainly focus on overt abuse and false information, which misses more mundane social media practices such as racial stereotyping that are equally popular and can be inadvertently harmful. Building on Stoever’s (2016) work on the “sonic color line,” this article problematizes sound, specifically, as a key element in racializing memetic practices on the popular short-video platform TikTok. We examine how humorous audio-visual memes about Covid-19 on TikTok contribute to social inequality by normalizing racial stereotyping, as facilitated through TikTok’s “Use This Sound” feature. We found that users’ appropriations of sounds and visuals on TikTok, in combination with the platform’s lack of clear and transparent moderation processes for humorous content, reinforce and (re)produce systems of advantage based on race. Our article contributes to remediating the consistent downplaying of humor that negatively stereotypes historically marginalized communities. It also advances work on race and racism on social media by foregrounding the sonification of race as means for racism’s evolving persistence, which represents a threat to social cohesion.

During times of crisis such as the Covid-19 pandemic, digital platforms are under public scrutiny to guarantee users' online safety and wellbeing. Following inconsistencies in how platforms moderate online content and behavior, governments around the world are putting pressure on them to curb the spread of illegal and lawful harmful content and behavior (e.g., UK’s Draft Online Safety Bill). These efforts, though, mainly focus on overt abuse and false information, which misses more mundane social media practices such as racial stereotyping that are equally popular and can be inadvertently harmful. Building on Stoever's (2016) work on the "sonic color line", this article problematizes sound, specifically, as a key element in racializing memetic practices on the popular short-video platform TikTok. We examine how humorous audio-visual memes about Covid-19 on TikTok contribute to social inequality by normalizing racial stereotyping, as facilitated through TikTok's "Use This Sound" feature. We found that users' appropriations of sounds and visuals on TikTok, in combination with the platform's lack of clear and transparent moderation processes for humorous content, reinforce and (re)produce systems of advantage based on race. Our article contributes to remediating the consistent downplaying of humor that negatively stereotypes historically marginalized communities. It also advances work on race and racism on social media by foregrounding the sonification of race as means for racism’s evolving persistence, which represents a threat to social cohesion.

YouTube's "up next" feature algorithmically selects, suggests, and displays videos to watch after the one that is currently playing. This feature has been criticized for limiting users' exposure to a range of diverse media content and information sources; meanwhile, YouTube has reported that they have implemented various technical and policy changes to address these concerns. However, there is little publicly available data to support either the existing concerns or YouTube's claims of having addressed them. Drawing on the idea of "platform observability", this article combines computational and qualitative methods to investigate the types of content that the algorithms underpinning YouTube's "up next" feature amplify over time, using three keyword search terms associated with sociocultural issues where concerns have been raised about YouTube’s role: "coronavirus", "feminism" and "beauty". Over six weeks, we collected the videos (and their metadata, including channel IDs) that were highly ranked in the search results for each keyword, as well as the highly ranked recommendations associated with the videos. We repeated this exercise for three steps in the recommendation chain and then examined patterns in the recommended videos (and the channels that uploaded the videos) for each query and their variation over time. We found evidence of YouTube’s stated efforts to boost "authoritative" media outlets, but at the same time, misleading and controversial content continues to be recommended. We also found that while algorithmic recommendations offer diversity in videos over time, there are clear "winners" at the channel level that are given a visibility boost in YouTube’s "up next" feature. However, these impacts are attenuated differently depending on the nature of the issue.

YouTube’s “up next” feature algorithmically selects, suggests, and displays videos to watch after the one that is currently playing. This feature has been criticized for limiting users’ exposure to a range of diverse media content and information sources; meanwhile, YouTube has reported that they have implemented various technical and policy changes to address these concerns. However, there is little publicly available data to support either the existing concerns or YouTube’s claims of having addressed them. Drawing on the idea of “platform observability,” this article combines computational and qualitative methods to investigate the types of content that the algorithms underpinning YouTube’s “up next” feature amplify over time, using three keyword search terms associated with sociocultural issues where concerns have been raised about YouTube’s role: “coronavirus,” “feminism,” and “beauty.” Over six weeks, we collected the videos (and their metadata, including channel IDs) that were highly ranked in the search results for each keyword, as well as the highly ranked recommendations associated with the videos. We repeated this exercise for three steps in the recommendation chain and then examined patterns in the recommended videos (and the channels that uploaded the videos) for each query and their variation over time. We found evidence of YouTube’s stated efforts to boost “authoritative” media outlets, but at the same time, misleading and controversial content continues to be recommended. We also found that while algorithmic recommendations offer diversity in videos over time, there are clear “winners” at the channel level that are given a visibility boost in YouTube’s “up next” feature. However, these impacts are attenuated differently depending on the nature of the issue.

Departing from Jessie Daniels’s 2013 review of scholarship on race and racism online, this article maps and discusses recent developments in the study of racism and hate speech in the subfield of social media research. Systematically examining 104 articles, we address three research questions: Which geographical contexts, platforms, and methods do researchers engage with in studies of racism and hate speech on social media? To what extent does scholarship draw on critical race perspectives to interrogate how systemic racism is (re)produced on social media? What are the primary methodological and ethical challenges of the field? The article finds a lack of geographical and platform diversity, an absence of researchers’ reflexive dialogue with their object of study, and little engagement with critical race perspectives to unpack racism on social media. There is a need for more thorough interrogations of how user practices and platform politics co-shape contemporary racisms.

Departing from Jessie Daniels’s 2013 review of scholarship on race and racism online, this article maps and discusses recent developments in the study of racism and hate speech in the subfield of social media research. Systematically examining 104 articles, we address three research questions: Which geographical contexts, platforms, and methods do researchers engage with in studies of racism and hate speech on social media? To what extent does scholarship draw on critical race perspectives to interrogate how systemic racism is (re)produced on social media? What are the primary methodological and ethical challenges of the field? The article finds a lack of geographical and platform diversity, an absence of researchers’ reflexive dialogue with their object of study, and little engagement with critical race perspectives to unpack racism on social media. There is a need for more thorough interrogations of how user practices and platform politics co-shape contemporary racisms., Departing from Jessie Daniels’s 2013 review of scholarship on race and racism online, this article maps and discusses recent developments in the study of racism and hate speech in the subfield of social media research. Systematically examining 104 articles, we address three research questions: Which geographical contexts, platforms, and methods do researchers engage with in studies of racism and hate speech on social media? To what extent does scholarship draw on critical race perspectives to interrogate how systemic racism is (re)produced on social media? What are the primary methodological and ethical challenges of the field? The article finds a lack of geographical and platform diversity, an absence of researchers’ reflexive dialogue with their object of study, and little engagement with critical race perspectives to unpack racism on social media. There is a need for more thorough interrogations of how user practices and platform politics co-shape contemporary racisms.