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Fig. 5. The Direction of Algorithmic Recommendations based on content that individual users watch and engage in and that peoples’ watching habits influence 70 percent of recommendations. Figure 6 shows the algorithmic advantage based on daily views. From this Figure, we can observe that the two out of the top three categories (Partisan Left, and Partisan Right) receive more recommendations than other categories irregardless of what category the seed channels belong to. Conversely, any other category does not get their channels suggested by the algorithm. In other words, the recommendation algorithm influences the traffic from all channels towards Partisan Left and Partisan Right channels, regardless of what category the channel that the users viewed belonged to. We can also observe this trend from a higher-level aggregate categorization, as is presented in Figure 7. The Figure affirms that channels that present left or centrist political content are advantaged by the recommendation algorithm, while channels that present content on the right are at a disadvantage. The recommendations algorithm advantages several groups to a significant extent. For example, we can see that when one watches a video that belongs to the Partisan Left category, the algorithm will present an estimated 3.4M impressions to the Center/Left MSM category more than it does the other way. On the contrary, we can see that the channels that suffer the most substantial disadvantages are again channels that fall outside mainstream media. Both right-wing and left-wing YouTuber channels are disadvantaged, with White Identitarian and Conspiracy channels being the least advantaged by the algorithm. For viewers of conspiracy channel videos, there are 5.5 million more recommendations to Partisan Right videos than vice versa. We should also note that right-wing videos are not the only disadvantaged groups. Channels discussing topics such as social justice or socialist view are disadvantaged by the recommendations algorithm as well. The common feature of Fig. 6. Algorithmic Advantage by Groups Fig. 7. High-level view of Algorithmic Advantages/Disadvantages in Rec- ommendation Impressions disadvantages channels is that their content creators are seldom broadcasting networks or mainstream journals. These channels are independent content creators. When it comes to the third claim regarding YouTube’s potential C3 - Radicalization Influence, i.e., YouTube’s al- gorithm influences users by exposing them to more extreme content than they would otherwise; this claim is also not supported by our data. On the contrary, the recommendation algorithm appears to restrict traffic towards extreme right- wing categories actively. The two most drastic examples arePDF Image | Algorithmic Extremism: Examining YouTube’s Rabbit Hole of Radicalization
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