Eddies: continuously adaptive query processing
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
WSQ/DSQ: a practical approach for combined querying of databases and the Web
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Partial results for online query processing
Proceedings of the 2002 ACM SIGMOD international conference on Management of data
Aurora: a new model and architecture for data stream management
The VLDB Journal — The International Journal on Very Large Data Bases
Pig latin: a not-so-foreign language for data processing
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Twitinfo: aggregating and visualizing microblogs for event exploration
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Tweets from Justin Bieber's heart: the dynamics of the location field in user profiles
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
An in-browser microblog ranking engine
ER'12 Proceedings of the 2012 international conference on Advances in Conceptual Modeling
uTrack: track yourself! monitoring information on online social media
Proceedings of the 22nd international conference on World Wide Web companion
An algorithm for local geoparsing of microtext
Geoinformatica
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Microblogs such as Twitter provide a valuable stream of diverse user-generated data. While the data extracted from Twitter is generally timely and accurate, the process by which developers 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 querying and extracting structure from 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, in addition to showcasing the power of the TweeQL language. Together these systems show the richness of content that can be extracted from Twitter.