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APPENDIX A CHANNEL CATEGORIZATION A. Channel Views and Formulas We have used several formulas in order to capture the flow of recommendations. The main concept in our study is the impression. Impression is an estimate for the number of times a viewer was presented with a recommendation. We count each of the top 10 recommendations for a video as an ”impression”. Only YouTube knows true impressions, so we use the following process create an estimate: • Everything else → Unclassified C. Hard Tags Hard tags are tags sources from external sources. Any combination of the following tags can be applied to a channel. Hard tags are for comparison between the categorization presented in this paper and other work, academic or otherwise, and also used to distinguish between YouTubers and TV or other mainstream media content. Tag Relevant impres- sions Channel views Daily channel views Relevant channel views Examples (A channel’s relevance %) x impressions The total number of video views since first of Jan- uary 2018 (channel views) * (days in the period videos have been recorded for the channel) (daily channel views) * (channel relevance %) Tag TV Content originally created for broadcast TV or cable D. Soft Tags Examples CNN, Vice Impressions An estimate for the number of times a viewer was presented with a recommendation. I.e. we count each of the top 10 recommendations for a video as an ”im- pression”. Only YouTube knows true impressions, so we use the following process create an estimate: Consider each combination of videos (e.g. Video A to Video B) (A to B impressions) = (recommendations from A to B) / (total recommendations from Video A) x (*A’s views) x (recommendations per video = 10) Mainstream News Reporting on newly received or noteworthy information. Widely accepted and self- identified as news (even if mostly opinion). Ap- pears in either https://www.adfontesmedia.com or https://mediabiasfactcheck.com. To tag they should have ¿ 30% focus on politics & culture. Fox News, Buz- zfeed News Ribeiro et al.’s alt-lite, alt-right, IDW As listed in Auditing Radicalization Pathways on YouTube [32] B. Tag Aggregation In order to create meaningful ideological categories, we have aggregated the tags assigned for each channel. In order to calculate the majority view, each soft tag is assessed independently. For each tag, the number of the reviewer with that rag must tally to more than half. Eighteen categories of soft tags, the soft tags defining left, center, and right, and the hard tags defining the media type, were aggregated for the visualization and data analysis. The following list informs which tags or tag combinations were aggregated to represent an ideology, rather than just a collection of tags. • White Identitarian → White Identitarian • MRA → MRA • Conspiracy → Conspiracy • Libertarian → Libertarian • AntiSJW and either Provocateur or PartisanRight → Provocative Anti-SJW • AntiSJW → Anti-SJW3 • Socialist → Socialist • ReligiousConservative → Religious Conservative • Social Justice or Anti-Whiteness → Social Justice • Left or Center ’hard’ tag and Mainstream News or Missing Link Media ’hard’ tag → Center/Left MSM • PartisanLeft → Partisan Left • PartisanRight → Partisan Right • AntiTheist → Anti-Theist 3This group has a significant overlap with the intellectual dark web-group as described by Ribero et al. (2019), Munger and Phillips (2019) Soft tags are a natural category for US YouTube content. Many traditional ways of dividing politics are not natural cate- gories that would accurately describe the politics of YouTube channels. In general, YouTubers are providing reaction and sensemaking on other channels or current events in the United States. We have created a list of categories that attempt to align the stands taken by the channels more naturally, expanding the categorization beyond the left, center, and right categories. The tag needs to be engaging in some way to the current meta-discussion about YouTube’s influence on politics. Our list of categories intends to cover major cultural topics and label channels to the best of our abilities. We have tried to find specific positions that could be mixed and aggregate in order to create categories that would represent ideologies. Our guiding principle is that, in order to apply one of these tags, one should be able to judge the channel by the channel content itself. It is important not to rely on an outside judgment about the channel’s content. It is also important to interpret the content with full context: there should be no mind-reading and no relying on a judgment from other sources. There should also be enough channels per each category. If the category is too niche, it should be excluded, unless it is essential for the radicalization pathway theory.PDF Image | Algorithmic Extremism: Examining YouTube’s Rabbit Hole of Radicalization
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