{"id":131,"date":"2019-01-29T16:05:24","date_gmt":"2019-01-29T16:05:24","guid":{"rendered":"https:\/\/wordpress.cs.vt.edu\/cs4984spring19\/?p=131"},"modified":"2019-02-07T09:03:42","modified_gmt":"2019-02-07T09:03:42","slug":"reflection-1-01-29-liz-dao","status":"publish","type":"post","link":"https:\/\/wordpress.cs.vt.edu\/cs4984spring19\/2019\/01\/29\/reflection-1-01-29-liz-dao\/","title":{"rendered":"Reflection #4 \u2013 [02\/07] \u2013 [Liz Dao]"},"content":{"rendered":"\n

Analyzing Right-wing YouTube Channels:<\/strong>
Hate, Violence and Discrimination<\/strong> S<\/strong><\/p>\n\n\n\n

Summary:<\/strong><\/p>\n\n\n\n

The paper investigates the\noccurrence of hateful content and discriminatory bias in right-wing channels.\nFirst, the authors examine the similarities and dissimilarities between\ncomments and video content on YouTube channels to see whether content creators\nexpress less, equally, or more hatred and discrimination than their audience.\nIn addition, the results of right-wing channels are compared to those of\nbaseline channels to check if extreme content is common on social media\nplatforms or more prominent in right-wing channels.<\/p>\n\n\n\n

The dataset consists of videos and\ncomments from 12 right-wing channels and 10 most subscribed channels on\nYouTube. The authors conduct a three-layered analysis through which they\nevaluate lexicon, topics and discriminatory bias in videos and comments from\nthe collected channels. <\/p>\n\n\n\n

The results suggest that right-wing\nchannels\u2019 topics are more concentrated, focusing on terrorism and war.\nMoreover, these channels have a higher percentage of negative word categories,\nsuch as aggression and violence compared to baseline channels. Surprisingly,\nthe level of bias against immigrants and LGBT people is comparable between\nright-wing and baseline channels. However, the negative bias against the Muslim\ncommunity is more noticeable in right-wing channels. The analysis also shows\nthat right-wing video hosts use negative words as often as commenters, yet the\nactual semantic fields vary. On the other hand, compared to the content\ncreators, the viewers of right-wing channels express a higher bias against LGBT\npeople and lower bias against Muslims in the comment section. <\/p>\n\n\n\n

Reflection:<\/strong><\/p>\n\n\n\n

It is obvious that the research, as\na whole, is partial and flawed. Not only that the title and the research\nquestions reflect the authors\u2019 strong presumption of the conservative section\nbut also the authors\u2019 choice of data is questionable. Why did they choose the\nwebsite InfoWars and Social Blade as a seed? Furthermore, the phrase \u201caccording\nto our understanding\u201d suggests their description of right-wing is not only\nambiguous but also potentially biased. The confusion carries over to their\nselection of baseline channels. Despite being selected from the \u201cnews and\npolitics\u201d category, the fact that the majority of the comments are related to\ngaming (RiceGum, PewDiePie, Minecraft) means those channels cover a much wider\nrange of topics. One of the channels is even called \u201cDramaAlert\u201d, which contributes\nmore than one-third of the total number of comments of baseline channels.\nHence, there is no surprise that entertaining videos contain more positive\nwords than those discussing serious, controversial topics. Rather, the research should have studied the extremist behavior in\npolitical predominant YouTube channels. It will be interesting to see if\nright-wing channels can be separated from the mix.<\/strong><\/p>\n\n\n\n

Even though the authors\u2019 bias\ndiscredit many of their findings, some analysis might still provide some insight\nand inspiration for future research. One worth noticing observation is that\nMuslims and terrorism overshadow other topics such as LGBT, illegal immigrants,\nanti-abortion, etc. Is terrorism always\nthe prominent focus? Has this topic gained more attention because of the series\nof recent attacks and the President\u2019s election campaign? It might be\ninteresting to see if the change in the trend of topics and people opinion\nthrough time, especially after a major incident. <\/strong><\/p>\n\n\n\n

Another surprising finding is the\ndissimilarity between the video hosts and the commenters. Despite the\ncomparable level of negativity, the variance in the semantic fields present in\nthe caption and in the comments in right-wing channels varies greatly across\nvideos. In another word, the viewers\u2019 response to the conservative videos is\nmore unpredictable and less affected by the sentiment of the hosts. The authors\nmentioned previous studies show hateful users \u201cmore negative, more profane and,\ncounter-intuitively, use fewer words associated with topics \u2026 \u201d Does this suggest right-wing channels\u2019\naudience is more hateful and aggressive? Do their comments remain as offensive\nand negative in other videos? Does a user\u2019s tendency to leave a hateful comment\ncorrelate to his\/her subscription? <\/strong><\/p>\n\n\n\n


<\/p>\n\n\n

<\/p>\n

<\/p>","protected":false},"excerpt":{"rendered":"

Analyzing Right-wing YouTube Channels: Hate, Violence and Discrimination S Summary: The paper investigates the occurrence of hateful content and discriminatory bias in right-wing channels. First, the authors examine the similarities and dissimilarities between comments and video content on YouTube channels to see whether content creators express less, equally, or more hatred and discrimination than their […]<\/p>\n","protected":false},"author":246,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"class_list":["post-131","post","type-post","status-publish","format-standard","hentry","category-uncategorized"],"jetpack_featured_media_url":"","_links":{"self":[{"href":"https:\/\/wordpress.cs.vt.edu\/cs4984spring19\/wp-json\/wp\/v2\/posts\/131","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/wordpress.cs.vt.edu\/cs4984spring19\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/wordpress.cs.vt.edu\/cs4984spring19\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/wordpress.cs.vt.edu\/cs4984spring19\/wp-json\/wp\/v2\/users\/246"}],"replies":[{"embeddable":true,"href":"https:\/\/wordpress.cs.vt.edu\/cs4984spring19\/wp-json\/wp\/v2\/comments?post=131"}],"version-history":[{"count":3,"href":"https:\/\/wordpress.cs.vt.edu\/cs4984spring19\/wp-json\/wp\/v2\/posts\/131\/revisions"}],"predecessor-version":[{"id":488,"href":"https:\/\/wordpress.cs.vt.edu\/cs4984spring19\/wp-json\/wp\/v2\/posts\/131\/revisions\/488"}],"wp:attachment":[{"href":"https:\/\/wordpress.cs.vt.edu\/cs4984spring19\/wp-json\/wp\/v2\/media?parent=131"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/wordpress.cs.vt.edu\/cs4984spring19\/wp-json\/wp\/v2\/categories?post=131"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/wordpress.cs.vt.edu\/cs4984spring19\/wp-json\/wp\/v2\/tags?post=131"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}