On the semantic annotation of places in location-based social networks
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
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As the world braces for the impact of the sequestration, international conflicts, and other decisions facing the US congress, people are wondering how their congressmen's decisions will affect their lives. Traditionally, to understand what issues a congressman found import, interested constituents would synthesize voting records, bills, and other disparate data sets to understand their congressman's habits. Fortunately, technology can now be used to integrate and display this information in an informative and visually appealing way. In response to this need to understand the behavior of congressmen, we have developed a mobile-based search and data mining application that provides users with the ability to analyze a large amount of social media data from Twitter, as well as data from the United States Congressional voting records. The application is focused on identifying patterns, anomalies, and associations between members of congress and external users to determine influential users within and outside Congress. This paper introduces the motivation behind the application -- Kongress - and then progresses into the system architecture. The applications features include the ability to search congressional tweets, votes, and bills, and a geospatial visualization of congressional tweets. We also demonstrate how a user could use Kongress to understand the motivation behind a congressman' decisions.