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Methods of knowledge discovery in tweets.

作者信息

Yoon Sunmoo, Bakken Suzanne

机构信息

School of Nursing and.

出版信息

NI 2012 (2012). 2012 Jun 23;2012:463. eCollection 2012.

Abstract
  1. to describe web mining methods for knowledge discovery in Tweets, and 2) to illustrate application of the methods using the topic of physical activity. Methods described include: 1) structure mining to discover structures (macro-, meso-, and micro-level) of Tweet networks using social network analysis, and 2) content mining to discover Tweet contents using n-gram based text analysis and sentiment analysis. Specific web mining tools for each step of the web mining process (e.g., NodeXL, ORA, Pajek, Weka) are detailed. Our novel application of web mining methods was useful in understanding multiple dimensions of physical activity. The methods that we applied may be useful to others wishing to mine social media for health-related purposes.
摘要

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Methods of knowledge discovery in tweets.
NI 2012 (2012). 2012 Jun 23;2012:463. eCollection 2012.
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本文引用的文献

1
Classifying disease outbreak reports using n-grams and semantic features.利用 n 元组和语义特征对疾病爆发报告进行分类。
Int J Med Inform. 2009 Dec;78(12):e47-58. doi: 10.1016/j.ijmedinf.2009.03.010. Epub 2009 May 15.
2
Finding and evaluating community structure in networks.在网络中寻找并评估社区结构。
Phys Rev E Stat Nonlin Soft Matter Phys. 2004 Feb;69(2 Pt 2):026113. doi: 10.1103/PhysRevE.69.026113. Epub 2004 Feb 26.

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