Conference Proceeding Article
Many event monitoring systems rely on counting known keywords in streaming text data to detect sudden spikes in frequency. But the dynamic and conversational nature of Twitter makes it hard to select known keywords for monitoring. Here we consider a method of automatically finding noun phrases (NPs) as keywords for event monitoring in Twitter. Finding NPs has two aspects, identifying the boundaries for the subsequence of words which represent the NP, and classifying the NP to a specific broad category such as politics, sports, etc. To classify an NP, we define the feature vector for the NP using not just the words but also the author's behavior and social activities. Our results show that we can classify many NPs by using a sample of training data from a knowledge-base. © 2012 ACM.
named entities, noun phrases, social media, twitter
Computer Sciences | Social Media
Data Management and Analytics
CIKM '12 Proceedings of the 21st ACM international conference on Information and knowledge management
City or Country
New York, USA
CHUA, Freddy Chong Tat; COHEN, William W.; BETTERRIDGE, Justin; and Ee-peng LIM.
Community-based classification of noun phrases in Twitter. (2012). CIKM '12 Proceedings of the 21st ACM international conference on Information and knowledge management. 1702-1706. Research Collection School Of Information Systems.
Available at: http://ink.library.smu.edu.sg/sis_research/3517
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