{"id":591,"date":"2021-04-13T13:38:29","date_gmt":"2021-04-13T05:38:29","guid":{"rendered":"http:\/\/langkunprc.com\/?p=591"},"modified":"2023-07-27T16:09:04","modified_gmt":"2023-07-27T08:09:04","slug":"disapprovalratingvixindexcovid19casesandtrumpstweetingagains","status":"publish","type":"post","link":"http:\/\/langkunprc.com\/index.php\/2021\/04\/13\/disapprovalratingvixindexcovid19casesandtrumpstweetingagains\/","title":{"rendered":"Disapproval rating, VIX Index, COVID-19 Cases and Trump\u2019s tweeting against China"},"content":{"rendered":"<p>Author: Kun Lang; Alexander Xincheng Li (Corresponding author)<\/p>\n<p>Abstract: The primary goal of this paper is to provide empirical evidence for how non-trade factors attribute to the China-US trade war. Trump\u2019s tweets provide us with a unique perspective. After analyzing 31,166 Trump\u2019s tweets, we have the following findings: (1) It\u2019s non-trade factors rather than trade-related factors that can significantly predict whether Trump posts negative tweets involving China\u2019s economic and trade issues. For every 1% increase in Trump\u2019s disapproval rating and VIX index, the likelihood of Trump posting negative tweets involving China&#8217;s economic and trade issues increases by 0.61% and 0.16% respectively. (2) Tweeting against China sometimes becomes a tool to divert domestic criticism. After the COVID-19 outbreak, the higher growth rate of cumulative COVID-19 confirmed cases, the higher likelihood of Trump tweeting against China. (3) Tweeting against China can win public support and attention. Holding everything else constant, the number of likes and retweets of negative tweets about China are 10.2% and 14.6% more than those of positive tweets about China.<\/p>\n<p>Keywords: trade war; Trump; Twitter; text analysis; COVID-19<\/p>\n<p>Full Length Article: <a href=\"http:\/\/langkunprc.com\/wp-content\/uploads\/2021\/04\/Disapproval-rating-VIX-index-COVID-19-cases-and-Trump\u2019s-tweeting-against-China.pdf\">Disapproval rating, VIX Index, COVID-19 Cases and Trump\u2019s tweeting against China<\/a>, Applied Economics Letters (SSCI, SJR Q3), online.<\/p>\n<a href=\"http:\/\/langkunprc.com\/wp-content\/uploads\/2021\/04\/Disapproval-rating-VIX-index-COVID-19-cases-and-Trump\u2019s-tweeting-against-China.pdf\" class=\"pdfemb-viewer\" style=\"\" data-width=\"max\" data-height=\"max\" data-toolbar=\"both\" data-toolbar-fixed=\"off\">Disapproval rating, VIX index, COVID-19 cases and Trump\u2019s tweeting against China<\/a>\n","protected":false},"excerpt":{"rendered":"<p>The primary goal of this paper is to provide empirical evidence for how non-trade factors attribute to the China-US trade war. Trump\u2019s tweets provide us with a unique perspective. After analyzing 31,166 Trump\u2019s tweets, we have the following findings: (1) It\u2019s non-trade factors rather than trade-related factors that can significantly predict whether Trump posts negative tweets involving China\u2019s economic and trade issues. For every 1% increase in Trump\u2019s disapproval rating and VIX index, the likelihood of Trump posting negative tweets involving China\u2019s economic and trade issues increases by 0.61% and 0.16% respectively. (2) Tweeting against China sometimes becomes a tool to divert domestic criticism. After the COVID-19 outbreak, the higher growth rate of cumulative COVID-19 confirmed cases, the higher likelihood of Trump tweeting against China. (3) Tweeting against China can win public support and attention. Holding everything else constant, the number of likes and retweets of negative tweets about China are 10.2% and 14.6% more than those of positive tweets about China.<\/p>\n","protected":false},"author":1,"featured_media":592,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_jetpack_memberships_contains_paid_content":false,"footnotes":"","jetpack_publicize_message":"","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":false,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2}},"categories":[97,1],"tags":[77,76],"class_list":["post-591","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-quan-qiu-hua-yan-jiu","category-yanjiuchengguo","tag-wenbenfenxi","tag-maoyimoca"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v25.3 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Disapproval rating, VIX Index, COVID-19 Cases and Trump\u2019s tweeting against China - \u90ce\u6606 Lang Kun<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"http:\/\/langkunprc.com\/index.php\/2021\/04\/13\/disapprovalratingvixindexcovid19casesandtrumpstweetingagains\/\" \/>\n<meta property=\"og:locale\" content=\"zh_CN\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Disapproval rating, VIX Index, COVID-19 Cases and Trump\u2019s tweeting against China - \u90ce\u6606 Lang Kun\" \/>\n<meta property=\"og:description\" content=\"The primary goal of this paper is to provide empirical evidence for how non-trade factors attribute to the China-US trade war. Trump\u2019s tweets provide us with a unique perspective. After analyzing 31,166 Trump\u2019s tweets, we have the following findings: (1) It\u2019s non-trade factors rather than trade-related factors that can significantly predict whether Trump posts negative tweets involving China\u2019s economic and trade issues. For every 1% increase in Trump\u2019s disapproval rating and VIX index, the likelihood of Trump posting negative tweets involving China\u2019s economic and trade issues increases by 0.61% and 0.16% respectively. (2) Tweeting against China sometimes becomes a tool to divert domestic criticism. After the COVID-19 outbreak, the higher growth rate of cumulative COVID-19 confirmed cases, the higher likelihood of Trump tweeting against China. (3) Tweeting against China can win public support and attention. Holding everything else constant, the number of likes and retweets of negative tweets about China are 10.2% and 14.6% more than those of positive tweets about China.\" \/>\n<meta property=\"og:url\" content=\"http:\/\/langkunprc.com\/index.php\/2021\/04\/13\/disapprovalratingvixindexcovid19casesandtrumpstweetingagains\/\" \/>\n<meta property=\"og:site_name\" content=\"\u90ce\u6606 Lang Kun\" \/>\n<meta property=\"article:author\" content=\"https:\/\/www.facebook.com\/profile.php?id=100013470904539\" \/>\n<meta property=\"article:published_time\" content=\"2021-04-13T05:38:29+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2023-07-27T08:09:04+00:00\" \/>\n<meta property=\"og:image\" content=\"http:\/\/langkunprc.com\/wp-content\/uploads\/2021\/04\/0dd7912397dda14439db19f252b068a40df486aa.jpg\" \/>\n\t<meta property=\"og:image:width\" content=\"640\" \/>\n\t<meta property=\"og:image:height\" content=\"360\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/jpeg\" 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