Visualizing User-Defined, Discriminative Geo-Temporal Twitter Activity
Visualizing User-Defined, Discriminative Geo-Temporal Twitter Activity
复制标题
可视化用户定义的、有区别的地理时态 Twitter 活动
DOI：
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发表时间：
2014
期刊：
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通讯作者：
Venkata Rama Kiran Garimella
中科院分区：
文献类型：
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作者：
Ingmar Weber;Venkata Rama Kiran Garimella
我们提出了一个系统，可视化地理时间的Twitter活动。我们的系统提供的显著特征包括：(i)用户在指定要可视化的数据子集方面有很大程度的自由；（ii）专注于“判别”模式，而不是大容量模式。具有精确GPS坐标的推文被分配到地理单元，并按(i)推文语言、（ii）推文主题、（iii）一周中的哪一天和（iv）一天中的时间进行分组。单元格的空间分辨率以数据驱动的方式确定，使用四叉树和递归分割。然后，用户可以选择查看周末晚上以“派对”为主题的英语推文数据。这个系统已经在卡塔尔（http://qtr.qcri.org/）的180万地理标记推文和纽约（http://nyc.qcri.org/）的480万地理标记推文上实现，并且可以很容易地扩展到其他城市/国家。
We present a system that visualizes geo-temporal Twitter activity. The distinguishing features our system offers include, (i) a large degree of user freedom in specifying the subset of data to visualize and (ii) a focus on *discriminative* patterns rather than high volume patterns. Tweets with precise GPS co-ordinates are assigned to geographical cells and grouped by (i) tweet language, (ii) tweet topic, (iii) day of week, and (iv) time of day. The spatial resolutions of the cells is determined in a data-driven manner using quad-trees and recursive splitting. The user can then choose to see data for, say, English tweets on weekend evenings for the topic "party". This system has been implemented for 1.8 million geo-tagged tweets from Qatar (http://qtr.qcri.org/) and for 4.8 million geo-tagged tweets from New York City (http://nyc.qcri.org/) and can be easily extended to other cities/countries.