Community-based classification of noun phrases in Twitter

Community-based classification of noun phrases in Twitter

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)...

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Bibliographic Details
Main Authors: CHUA, Freddy Chong Tat, COHEN, William W., BETTERRIDGE, Justin, Ee-peng LIM
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2012
Subjects:
Named entities
Noun phrases
Social media
Twitter
Computer Sciences
Social Media
Online Access:https://ink.library.smu.edu.sg/sis_research/3517
https://ink.library.smu.edu.sg/context/sis_research/article/4518/viewcontent/C32___Community_Based_Classification_of_Noun_Phrases_in_Twitter__CIKM2012_.pdf
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Institution: Singapore Management University
Language: English
Description
Summary: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.

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