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| Extracting Emotion Tags from Comments of Microblog Commodities |
Bocheng Li1,Yunqiu Zhang1( ),Kaixi Yang2 |
1 College of Public Health, Jilin University, Changchun 130021, China
2 International School of Information Science & Engineering, Dalian University of Technology, Dalian 116620, China; |
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Abstract [Objective] This paper proposes a new method to collect emotion tags from microblog comments, aiming to improve the performance of feature-level data extraction. [Methods] First, we divided the evaluation units and extracted the explicit tags based on the dependency parsing and the extraction rules. Then, we revealed the implicit expression relationship in comments with the NodeRank algorithm. Finally, we retrieved the implicit tags to improve the accuracy of emotion tag retrieval. [Results] We examined the proposed method with the real online comments. The overall precision of the method was 83.6%, the recall rate was 87.1%, and the F value was 85.3%, which were better than the traditional methods. [Limitations] We did not fully utilize users’ general emotional expressions. [Conclusions] The proposed method based on dependency parsing and NodeRank algorithm can extract emotion tags effectively.
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Received: 19 December 2018
Published: 23 October 2019
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