JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE) ›› 2014, Vol. 49 ›› Issue (11): 43-50.doi: 10.6040/j.issn.1671-9352.3.2014.016

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Comparative study of methods for Micro-blog sentiment evaluation tasks

SUN Song-tao, HE Yan-xiang, CAI Rui, LI Fei, HE Fei-yan   

  1. Computer School, Wuhan University, Wuhan 430072, Hubei, China
  • Received:2014-08-28 Revised:2014-10-17 Online:2014-11-20 Published:2014-11-25

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Abstract: This paper was a report on COAE2014. The methods to solve the tasks were described, and deeply analyzed by referring to the results. There were 5 different tasks in this year's contest, 3 of which were related to Micro-blog and were focused in this paper. In the new sentiment words discovering and determining of Micro-blog task, the important processes was extracting candidate new words by using the alignment results of Google translation service, then filtering frequent words by ranking their PMI. In the sentiment classification of Micro-blog task, two different methods were used to solve the problem. One was based on sentiment lexicon which was the traditional method. The other was based on CRFs combining the sentiment lexicon. The last task was to extract opinion aspects from Micro-blog and then to determine the sentiment on them. Firstly, the phrases that represent the products' name and aspects were extracted according the betweenness and closeness of the complex network formed by all the nouns in two steps respectively. Then, three methods were introduced to extract the exact product aspects and its sentiment. The first one was based on simple rules which extracted phrases in the sliding window. The other two were supervised learning procedures which were all based on CRFs.

Key words: sentiment analysis, CRFs, Micro-blog, aspect sentiment extraction, complex network

CLC Number: 

  • TP391
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