Algorithmic extremism: Examining YouTube's rabbit hole of radicalization

Abstract

The role that YouTube and its behind-the-scenes recommendation algorithm plays in encouraging online radicalization has been suggested by both journalists and academics alike. This study directly quantifies these claims by examining the role that YouTubes algorithm plays in suggesting radicalized content. After categorizing nearly 800 political channels, we were able to differentiate between political schemas in order to analyze the algorithm traffic flows out and between each group. After conducting a detailed analysis of recommendations received by each channel type, we refute the popular radicalization claims. To the contrary, these data suggest that YouTubes recommendation algorithm actively discourages viewers from visiting radicalizing or extremist content. Instead, the algorithm is shown to favor mainstream media and cable news content over independent YouTube channels with slant towards left-leaning or politically neutral channels. Our study thus suggests that YouTubes recommendation algorithm fails to promote inflammatory or radicalized content, as previously claimed by several outlets.

Beyond (Mis)Representation: Visuals in COVID-19 Misinformation

“…Findings have varied widely. While some have found conspiracy theories, climate denial, and extremist content common on YouTube (Allgaier 2019; Lewis 2018), others have found that YouTube’s algorithms are promoting mainstream content (Bounegru et al 2020; Ledwich and Zaitsev 2020). More relevant here, Marchal et al (2020) found YouTube’s search algorithm prioritizing COVID-19-related content from legitimate institutional sources.…”

The strategic use of incivility in contemporary politics. The case of the 2018 Italian general election on Facebook

“…Nevertheless, critical approaches stress that web platforms can accentuate antagonism and hostility among participants, damaging online discussion's potential for upholding the public sphere (Dahlberg, 2001). This "dual nature" of the internet has manifested since the very beginning of online communication (Ledwich & Zaitsev, 2019), where "flame-wars" (Kayany, 1998) and trolling behavior were already common practice in the everyday life of online communities. With the success of social media, behaviors previously confined to Usenet message boards and limited IRC channels such as inflammatory behavior, antisocial messaging and polarized extremism (Ledwich & Zaitsev, 2019) have become commonplace in the public consciousness.…”

“…This "dual nature" of the internet has manifested since the very beginning of online communication (Ledwich & Zaitsev, 2019), where "flame-wars" (Kayany, 1998) and trolling behavior were already common practice in the everyday life of online communities. With the success of social media, behaviors previously confined to Usenet message boards and limited IRC channels such as inflammatory behavior, antisocial messaging and polarized extremism (Ledwich & Zaitsev, 2019) have become commonplace in the public consciousness. Thus, while everyday political discussion might help participants to learn and understand matters of public concerns (Rossini, 2019), narratives emerging on social media do not necessarily seem civil (Rohlinger & Williams, 2019).…”

Recommender systems and the amplification of extremist content

“…We contribute to this debate in two ways: firstly, we conduct an empirical analysis of interactions of recommendation systems and far-right content on three platforms-YouTube, Reddit, and Gab. This analysis provides a novel contribution by being the first study to account for personalisation in an experimental setting, which has been noted as a limitation by previous empirical research (Ledwich and Zaitsev, 2019;Ribeiro et al, 2019). We find that one platform-YouTube-does promote extreme content after interacting with far-right materials, but the other two do not.…”