Processing and visualizing the data in tweets Citation
نویسندگان
چکیده
Microblogs such as Twitter provide a valuable corpus of diverse user-generated content. While the data extracted from Twitter is generally timely and accurate, the process by which developers currently extract structured data from the tweet stream is ad-hoc and requires reimplementation of common data manipulation primitives. In this paper, we present two systems for extracting structure from and querying Twitter-embedded data. The first, TweeQL, provides a streaming SQL-like interface to the Twitter API, making common tweet processing tasks simpler. The second, TwitInfo, shows how end-users can interact with and understand aggregated data from the tweet stream (as well as showcasing the power of the TweeQL language). Together these systems show the richness of content that can be extracted from Twitter.
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