{"id":506,"date":"2019-02-07T13:53:08","date_gmt":"2019-02-07T13:53:08","guid":{"rendered":"https:\/\/wordpress.cs.vt.edu\/cs4984spring19\/?p=506"},"modified":"2019-02-07T13:53:10","modified_gmt":"2019-02-07T13:53:10","slug":"reading-reflection-4-02-07-alon-bendelac","status":"publish","type":"post","link":"https:\/\/wordpress.cs.vt.edu\/cs4984spring19\/2019\/02\/07\/reading-reflection-4-02-07-alon-bendelac\/","title":{"rendered":"Reading Reflection #4 &#8211; [02\/07] &#8211; [Alon Bendelac]"},"content":{"rendered":"\n<p class=\"wp-block-paragraph\"><strong>Summary<\/strong>:<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">This paper\nstudies the presence of hateful, violent, and discriminatory content in YouTube\nchannels of two categories: right-wing and baseline. The study analyzes the\nlexicon, topics, and implicit biases in the text of the videos. More specifically,\nthe text in video titles, captions, and comments were studied. The dataset used\nconsists of over 7,000 videos and 17 million comments. It was found the right-wing\nchannels contain more \u201cnegative\u201d words, contain more topics about war and terrorism,\nand are more discriminating against minorities such as Muslims and the LGBT\ncommunity.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Reflection<\/strong>:<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Compare against left-wing channels<\/strong>: Instead of comparing right-wing YouTube\nchannels to the rest of YouTube, I think the study should have narrowed their\nbaseline to a set of left-wing channels. This would make the comparison more symmetric\nand would emphasize the results.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Video Transcript<\/strong>: A significant aspect of a YouTube\nvideo is the transcript (i.e. what is being said). I think if the study\nincluded that they would have a lot more data to look at.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">I think the\nintroduction could be improved. Although the idea of the study is clear, the\nintroduction did not specify a motivation for studying this topic. It did not\nstate in what kind of real-world application this study can be used. Also,\nrelated work should have been at the beginning of the paper, not at the end.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">In addition\nto looking at specific words, I think the study should look at the presence of n-grams.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Data over time<\/strong>: Is there a pattern to the findings\nwhen looked over an extended time period? I think it would be interesting to do\na similar study that looks at how the contents of right-wing channels change\nover time, and to see how the findings relate to real-world events.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">In order to\nstudy the content of the video itself, and not just the text surrounding it, I\nthink crowdsourcing could be used to label videos with tags that describe their\ncontents. This dataset could be used to study any other classifications of\nYouTube videos.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Blocked words<\/strong>: Channels can create a list of words\nthat they want to review before allowing in the comments section. This might limit\nwhat users are able to say. Do the right-wing channels block more, or less\ncomments than the baseline channels? How might this impact the results of the\nstudy?<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Verified channels<\/strong>: Is the percentage of channels that\nare verified different in the two categories (right-wing and baseline)?<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Summary: This paper studies the presence of hateful, violent, and discriminatory content in YouTube channels of two categories: right-wing and baseline. The study analyzes the lexicon, topics, and implicit biases in the text of the videos. More specifically, the text in video titles, captions, and comments were studied. The dataset used consists of over 7,000 [&hellip;]<\/p>\n","protected":false},"author":247,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"class_list":["post-506","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\/506","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\/247"}],"replies":[{"embeddable":true,"href":"https:\/\/wordpress.cs.vt.edu\/cs4984spring19\/wp-json\/wp\/v2\/comments?post=506"}],"version-history":[{"count":1,"href":"https:\/\/wordpress.cs.vt.edu\/cs4984spring19\/wp-json\/wp\/v2\/posts\/506\/revisions"}],"predecessor-version":[{"id":507,"href":"https:\/\/wordpress.cs.vt.edu\/cs4984spring19\/wp-json\/wp\/v2\/posts\/506\/revisions\/507"}],"wp:attachment":[{"href":"https:\/\/wordpress.cs.vt.edu\/cs4984spring19\/wp-json\/wp\/v2\/media?parent=506"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/wordpress.cs.vt.edu\/cs4984spring19\/wp-json\/wp\/v2\/categories?post=506"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/wordpress.cs.vt.edu\/cs4984spring19\/wp-json\/wp\/v2\/tags?post=506"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}