全球智库信息集成服务系统(G2TT): DP14455 Terrorist Attacks, Cultural Incidents and the Vote for Radical Parties: Analyzing Text from Twitter

G2TT

来源类型	Discussion paper
规范类型	论文
来源ID	DP14455
	DP14455 Terrorist Attacks, Cultural Incidents and the Vote for Radical Parties: Analyzing Text from Twitter
	Francesco Giavazzi; Giacomo Lemoli; Gaia Rubera; Felix Iglhaut
发表日期	2020-02-29
出版年	2020
语种	英语
摘要	We study the role of perceived threats from cultural diversity induced by terrorist attacks and a salient criminal event on public discourse and voters' support for far-right parties. We first develop a rule which allocates Twitter users in Germany to electoral districts and then use a machine learning method to compute measures of textual similarity between the tweets they produce and tweets by accounts of the main German parties. Using the dates of the aforementioned exogenous events we estimate constituency-level shifts in similarity to party language. We find that following these events Twitter text becomes on average more similar to that of the main far-right party, AfD, while the opposite happens for some of the other parties. Regressing estimated shifts in similarity on changes in vote shares between federal elections we find a significant association. Our results point to the role of perceived threats on the success of nationalist parties.
主题	Macroeconomics and Growth ; Public Economics
关键词	National elections Political parties Text analysis Social media Terrorism
URL	https://cepr.org/publications/dp14455
来源智库	Centre for Economic Policy Research (United Kingdom)
资源类型	智库出版物
条目标识符	http://119.78.100.153/handle/2XGU8XDN/543354
推荐引用方式 GB/T 7714	Francesco Giavazzi,Giacomo Lemoli,Gaia Rubera,et al. DP14455 Terrorist Attacks, Cultural Incidents and the Vote for Radical Parties: Analyzing Text from Twitter. 2020.