PDF Publication Title:
Text from PDF Page: 004
We added emerging channels by following the YouTube recommendation algorithm, which suggests similar content and which fit the criteria and passed our threshold. We can con- ceptualize the recommendation algorithm as a type of snowball sampling, a common technique applied in social sciences when one is conducting interview-based data collection but also in the analysis of social networks. Each source is ”requested” to nominate a few candidates that would be of interest to the study. The researcher follows there recommendations until the informants reveal no new information or the inclusion criteria are met (e.g., channels become too marginal, or content is not political). In our case, there is a starting point; a channel acts as a node in the network. Each connected channel (e.g., node) in the network is visited. Depending on the content of the channel, it is either added to the collection of channels or discarded. Channels are visited until there are no new channels, or the new channels do not fit the original selection criteria [42]. B. The Categorization Process The categorization of YouTube channels was a non-trivial task. Activist organizations provide lists and classifications, but many of them are unreliable. For example, there are several controversies around the lists of hate groups discussed by the Southern Poverty Law Center (SPLC) [43]. Also, there seems to be a somewhat contentious relationship between the Anti- Defamation League and YouTubers [44] [45]. We decided to create our categorization, based on multiple existing sources. First, one has several resources to categorize mainstream or alternative media outlets. Mainstream media such as CNN or Fox News have been studied and categorized over time by various outlets [46] [47]. In our study, we applied two sites that provide information on the political views of mainstream media outlets: Ad Fontes Media and Media Bias Factcheck. Neither website is guaranteed to be unbiased, but by cross- referencing both, one can come to a relatively reliable catego- rization on the political bias of the major news networks. These sites covered the fifty largest mainstream channels, which make up for almost 80 percent of all YouTube views. Nevertheless, the majority of the political YouTube channels were not included in sources categorizing mainstream outlets. After reviewing the existing literature on political YouTube and the categorization created by authors such as Ribero et al. (2019) or Munger and Philips (2019), we decided to create a new categorization. Our study strives for a granular and precise classification to facilitate a deep dive into the political subcultures of YouTube, and the extant categories were too narrow in their scope. We decided to apply on both a high-level left-center-right political classification for high- level analysis and create a more granular distinction between eighteen separate labels, described shortly in Table I or at length in Appendix A-D). In addition to these ’soft tags,’ we applied a set of so-called ’hard tags.’ These additional tags allowed us to differentiate between YouTube channels that were part of mainstream media outlets and independent YouTubers. The hard tags TABLE I CATEGORIZATION SOFT TAGS AND EXAMPLES Tag Conspiracy A channel that regularly promotes a variety of conspiracy theories. Libertarian Political philosophy with liberty as the main principle. Anti-SJW Have a significant focus on criticizing ”Social Justice” (see next category) with a positive view of the marketplace of ideas and discussing controversial topics. Social Justice Promotes identity Politics and inter- sectionality White Identitarian Identifies-with/is-proud-of the superiority of ”whites” and western civilization. Educational Channel that mainly focuses on educa- tion material. Late Night Talk shows Channel with content pre- sented humorous monologues about the daily news. Partisan Left Focused on politics and exclusively critical of Republicans. Partisan Right Channel mainly focused on politics and exclusively critical of Democrats, supporting Trump. Anti-theist Self-identified atheist who are also ac- tively critical of religion. Religious Conservative A channel with a focus on promoting Christianity or Judaism in the context of politics and culture. Socialist (Anti-Capitalist) Focus on the problems of capitalism. Revolutionary Endorses the overthrow of the current political system. Provocateur Enjoys offending and receiving any kind of attention. MRA (Mens Rights Activist) Focus on advocating for rights for men. Missing Link Media Channels not large enough to be considered ”mainstream.” State Funded Channels funded by governments. Anti-Whiteness A subset of Social Justice that in addition to intersectional beliefs about race Examples X22Report, The Next News Net- work Reason, John Stossel, The Cato Institute Sargon of Akkad, Tim Pool Peter Coffin, hbomberguy NPIRADIX (Richard Spencer) TED, SoulPancake Last Week Tonight, Trevor Noah The Young Turks, CNN Fox News, Can- dace Owens CosmicSkeptic, Matt Dillahunty Ben Shapiro, PragerU Richald Wolf, NonCompete Libertarian Socialist Rants, Jason Unruhe StevenCrowder, MILO Karen Straughan Vox, NowThis News PBS NewsHour, Al Jazeera, RT African Diaspora News Channel are discussed in more detail in Appendix A. The difference between ’soft’ and ’hard’ tags is that hard tags were based on external sources, whereas the soft tags were based on the content analysis of the labelers. The tagging process allowed each channel to be character- ized by a maximum of four different tags to create meaningful and fair categories for the content. In addition to labeling created by the two authors, we recruited an additional vol- unteer labeler, who was well versed in the YouTube political sphere, and whom we trusted to label channels by their existing content accurately. When two or more labelers defined a channel by the same label, that label was assigned to the channel. When the labelers disagreed and ended in a draw situation, the tag was not assigned. The majority was needed for a tag to be applied. The visual analysis in Figure 1 shows the intraclass corre-PDF Image | Algorithmic Extremism: Examining YouTube’s Rabbit Hole of Radicalization
PDF Search Title:
Algorithmic Extremism: Examining YouTube’s Rabbit Hole of RadicalizationOriginal File Name Searched:
1912-11211.pdfDIY PDF Search: Google It | Yahoo | Bing
Cruise Ship Reviews | Luxury Resort | Jet | Yacht | and Travel Tech More Info
Cruising Review Topics and Articles More Info
Software based on Filemaker for the travel industry More Info
The Burgenstock Resort: Reviews on CruisingReview website... More Info
Resort Reviews: World Class resorts... More Info
The Riffelalp Resort: Reviews on CruisingReview website... More Info
CONTACT TEL: 608-238-6001 Email: greg@cruisingreview.com (Standard Web Page)