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! Chévere! Text-Based Twitter Patterns from Venezuelan Food Shortages

机译:!切韦尔!委内瑞拉粮食短缺带来的基于文本的Twitter模式

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Social media data from countries having challenges to free speech is a reliable form of journalism. An analysis is conducted to examine the social media response to the Venezuelan food shortages. Over 37,000 filtered Spanish tweets from the city of Caracas, Venezuela were used to observe reactions within each of the city's five municipalities. The number of tweets from December 2014 to October 2016 (23 months) is compared to the top trending tweet from July 19, 2017. Machine learning techniques show that certain tweets may be linked to a municipality within a 10 km radius. Tweet volume over almost two years indicates the significance of the shortages among the Venezuelan people engaged in the event.
机译:来自面临言论自由挑战的国家/地区的社交媒体数据是一种可靠的新闻形式。进行了分析,以检查社交媒体对委内瑞拉粮食短缺的反应。来自委内瑞拉加拉加斯市的超过37,000条经过过滤的西班牙推文被用来观察该市五个城市中每个城市的反应。将2014年12月至2016年10月(23个月)的推文数量与2017年7月19日以来的热门趋势推文进行了比较。机器学习技术显示,某些推文可能与半径10公里以内的自治市相关。近两年来的推文数量表明参与该事件的委内瑞拉人中短缺的重要性。

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