TwiNER: named entity recognition in targeted twitter stream

Many private and/or public organizations have been reported to create and monitor targeted Twitter streams to collect and understand users’ opinions about the organizations. Targeted Twitter stream is usually constructed by filtering tweets with user-defined selection criteria (e.g., tweets published by users from a selected region, or tweets that match one or more predefined keywords). Targeted Twitter stream is then monitored to collect and understand users’ opinions about the organizations. There is an emerging need for early crisis detection and response with such target stream. Such applications require a good named entity recognition (NER) system for Twitter, which is able to automatically discover emerging named entities that is potentially linked to the crisis. In this paper, we present a novel 2-step unsupervised NER system for targeted Twitter stream, called TwiNER. In the first step, it leverages on the global context obtained from Wikipedia and Web N-Gram corpus to...

• Type: Journal
• Year: 2012
• Where: SIGIR
• Authors: Chenliang Li, Jianshu Weng, Qi He, Yuxia Yao, Anwitaman Datta, Aixin Sun, Bu-Sung Lee
• Keywords: Dynamic Programming Algorithm, Entity Recognition, Hp Labs, Information Technology, SIGIR 2012