Community-based classification of noun phrases in Twitter

• 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
• Institution: Singapore Management University

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.