旅行趋势：社交蝴蝶还是飞行常客？
Traveling Trends: Social Butterflies or Frequent Fliers?
摘要：
热门话题是在社交媒体上引起集体关注的在线对话。它们不断变化，往往反映了现实世界中发生的外部事件。趋势在空间和时间上是局部化的，因为它们是由特定地理区域的活动驱动的，这些活动是交通和信息流的来源。独立地考虑，趋势和地理在最近的在线社交媒体文献中已经讨论过;尽管到目前为止，还没有做什么来描述趋势和地理之间的关系。在这里，我们调查了2013年50天内美国63个主要地点Twitter上的11000多个主题。这些数据使我们能够研究趋势的起源和路径，它们如何在地方一级竞争流行，以成为国家一级的赢家，以及它们在不同地理区域的生产和消费背后的动力。我们确定了两类主要的趋势主题：那些在本地出现的，与三个不同的地理集群（东海岸，中西部和西南部）相吻合;以及那些从几个大都市地区出现的全球性的，与该国的主要空中交通枢纽相吻合。这些中心充当潮流引领者，产生最终在国家一级流行的话题，并推动全国范围的对话。这提出了一个有趣的猜想，将信息传播与疾病进行了类比：趋势通过飞机传播比通过互联网传播更快吗？
英文摘要：
Trending topics are the online conversations that grab collective attention on social media. They are continually changing and often reflect exogenous events that happen in the real world. Trends are localized in space and time as they are driven by activity in specific geographic areas that act as sources of traffic and information flow. Taken independently, trends and geography have been discussed in recent literature on online social media; although, so far, little has been done to characterize the relation between trends and geography. Here we investigate more than eleven thousand topics that trended on Twitter in 63 main US locations during a period of 50 days in 2013. This data allows us to study the origins and pathways of trends, how they compete for popularity at the local level to emerge as winners at the country level, and what dynamics underlie their production and consumption in different geographic areas. We identify two main classes of trending topics: those that surface locally, coinciding with three different geographic clusters (East coast, Midwest and Southwest); and those that emerge globally from several metropolitan areas, coinciding with the major air traffic hubs of the country. These hubs act as trendsetters, generating topics that eventually trend at the country level, and driving the conversation across the country. This poses an intriguing conjecture, drawing a parallel between the spread of information and diseases: Do trends travel faster by airplane than over the Internet?
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
