{"id":202,"date":"2019-01-31T04:14:51","date_gmt":"2019-01-31T04:14:51","guid":{"rendered":"https:\/\/wordpress.cs.vt.edu\/cs4984spring19\/?p=202"},"modified":"2019-01-31T04:14:53","modified_gmt":"2019-01-31T04:14:53","slug":"reflection-2-01-30-jonathan-alexander","status":"publish","type":"post","link":"https:\/\/wordpress.cs.vt.edu\/cs4984spring19\/2019\/01\/31\/reflection-2-01-30-jonathan-alexander\/","title":{"rendered":"[Reflection #2] &#8211; [01\/30] -[Jonathan Alexander]"},"content":{"rendered":"\n<p class=\"wp-block-paragraph\"><strong>Overview<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">This paper is about a study conducted to characterize\nantisocial behavior in large online discussion communities. The study aims to\nanswer three questions: are there users that only become antisocial later in\ntheir community life, does a community\u2019s reaction to antisocial behavior\nimprove the behavior, and can antisocial users be identified before they cause\nany issues in the community? The study used CNN.com, Breitbart.com, and IGN.com\nto conduct their analysis of online discussion communities. They found that users\nwho were eventually banned from these communities concentrated their efforts on\na smaller number of threads, wrote worse than other users over time, and were\nexacerbated by other users over time. Using these conclusions the author\ncreated a classifier to try to identify negative users before the antisocial\nbehavior got them banned by the websites moderators.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Reflection<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\"><li>The websites chosen by the author for use in the\nstudy are known to house biased and controversial discussions. The banning of\nusers or antisocial behavior on these websites may be inherent to the nature of\nthe topics being discussed. This is specifically true on CNN.com and\nBreitbart.com. Given the polarizing nature of politics, these websites are not\nso much discussion communities and may be more susceptible to users engaging in\nundesired behaviors more so than other discussion communities that are actually\ncommunities. Websites such as Breitbart.com have content that is inflammatory to\nsome and may lead to outbursts that this study would call antisocial.<\/li><li>The paper also states that users that violate\nthe community norms are eventually permanently banned from the discussion\ncommunity. The author uses this as their \u201cground truth\u201d for analyzing antisocial\nbehavior online. However, communities such as Breitbart.com and CNN.com likely\ncontain many users with similar views and biases. A user that violates these\nnorms and is banned may not necessarily be displaying antisocial behavior. It\nis also possible that the banned user disagreed with the views of the community\nor did not hold their same beliefs. These differences between users and the\nspecific community they engaged with could have led to them violating that\ncommunities norms and being banned. That does not mean their behavior was\nantisocial, rather it could have just been following a different set of norms\nthan that found in the subset of society on Breitbart.com or CNN.com. I think\nan interesting question would be <strong>what portion\nof users banned from websites like Breitbart.com and CNN.com help viewpoints\nopposing the majority of users on those platforms?<\/strong><\/li><li>The paper employs the use of human workers to\nlabel the appropriateness of a post. Doing this introduces bias into the\nratings inherent with the introduction of humans. The three websites chosen\nrepresent three widely different communities, that are each different in some\nway from the mainstream culture. Asking workers to rate these posts who have no\nexperience with the community they are rating or what is appropriate for that\nsetting has the potential to produce inaccurate or biased ratings as each of\nthe workers has to rely on their own opinions and beliefs to decide what is\nappropriate.<\/li><li>Later in the paper they use the fact that those\nwho are banned from websites tend to write posts that are less similar than the\nothers on the forum. I do not think this is a clear indication the posts\nincluded antisocial behavior. If the users are very different from the community\nthey are communicating with that may be the reason they are banned. It could be\na difference of opinion or personality, not necessarily antisocial behavior. <\/li><li>The author also uses the rate of post deletion\nto predict banning and characterize the user as antisocial. However, a high\nrate of post deletion could predict banning as it shows that the moderator, who\neventually bans the user, does not like having that user\u2019s content on their forum.\nUsing this as a predictor could be gauging the moderator\u2019s opinion of the user\nmore than any antisocial behavior the user is displaying. Furthermore, user banning,\nas a metric of antisocial behavior seems like it could miss many cases. Being banned\nfrom an online community, especially those that act as echo chambers for a\nsimilar set of opinions, does not necessarily mean that the behavior was\nantisocial. <strong>How can we measure\nantisocial behavior without including differences between users and the community?<\/strong><\/li><\/ul>\n\n\n\n<p class=\"wp-block-paragraph\">I think this paper addresses an\nimportant issue as online discussion and discourse becomes more prevalent. I\nfound some issue with how the study was conducted as it seems they are\nmeasuring how different some users are from the overall community and how the\nmoderator feels about them more so than their antisocial behavior. By using the\ndeletion of posts and difference from other posts as the main measures of\nantisocial behavior, they are really measuring the moderator\u2019s view of the user\nand how much they stick out from the overall community. The article states that\nif becomes harder for their classifier to predict if a user will be banned the\nfurther in time it is from when they are actually banned. This helps illustrate\nthat they are measuring the moderator opinion of the user rather than the underlying\nantisocial behavior as it makes sense that a moderator will delete more of the\nusers posts (their main feature in classification) soon before they ban the\nuser. <strong>For future research,<\/strong> <strong>analysis of the content of posts by users\nwho display antisocial behavior over the life of their account would be\ninteresting to see how this behavior begins and how community features interact\nwith this behavior.<\/strong><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Overview This paper is about a study conducted to characterize antisocial behavior in large online discussion communities. The study aims to answer three questions: are there users that only become antisocial later in their community life, does a community\u2019s reaction to antisocial behavior improve the behavior, and can antisocial users be identified before they cause [&hellip;]<\/p>\n","protected":false},"author":256,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"class_list":["post-202","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\/202","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\/256"}],"replies":[{"embeddable":true,"href":"https:\/\/wordpress.cs.vt.edu\/cs4984spring19\/wp-json\/wp\/v2\/comments?post=202"}],"version-history":[{"count":1,"href":"https:\/\/wordpress.cs.vt.edu\/cs4984spring19\/wp-json\/wp\/v2\/posts\/202\/revisions"}],"predecessor-version":[{"id":203,"href":"https:\/\/wordpress.cs.vt.edu\/cs4984spring19\/wp-json\/wp\/v2\/posts\/202\/revisions\/203"}],"wp:attachment":[{"href":"https:\/\/wordpress.cs.vt.edu\/cs4984spring19\/wp-json\/wp\/v2\/media?parent=202"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/wordpress.cs.vt.edu\/cs4984spring19\/wp-json\/wp\/v2\/categories?post=202"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/wordpress.cs.vt.edu\/cs4984spring19\/wp-json\/wp\/v2\/tags?post=202"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}