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Data Analysis and Knowledge Discovery  2017, Vol. 1 Issue (2): 73-79    DOI: 10.11925/infotech.2096-3467.2017.02.10
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Analyzing Sentiments of Micro-blog Posts Based on Support Vector Machine
Shuang Yang(),Fen Chen
School of Economics and Management, Nanjing University of Science & Technology, Nanjing 210094, China
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[Objective] This paper proposes a new method based on the Support Vector Machine to monitor online public opinion. [Methods] We extracted fourteen linguistic characteristics of the micro-blog posts and analysed their sentiments with Support Vector Machine. [Results] The precision, recall and F value of the proposed method were 82.40%, 81.91%, and 82.10%, respectively. [Limitations] The size of training corpus needs to be expanded. [Conclusions] The proposed method could effectively analyze sentiments of micro-blog posts.

Key wordsMicroblog      Sentiment Analysis      Support Vector Machine      Parsing     
Received: 29 August 2016      Published: 27 March 2017

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Shuang Yang,Fen Chen. Analyzing Sentiments of Micro-blog Posts Based on Support Vector Machine. Data Analysis and Knowledge Discovery, 2017, 1(2): 73-79.

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