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A transformation method for aspect-based sentiment analysis / Đặng Văn Thìn,...
// Tạp chí Tin học và Điều khiển học Vol.34, No 4/2018 tr.323-333 Along with the explosion of user reviews on the Internet, sentiment analysis has becomeone of the trending research topics in the field of natural language processing. In the last five years,many shared tasks were organized to keep track of the progress of sentiment analysis for various lan-guages. In the Fifth International Workshop on Vietnamese Language and Speech Processing (VLSP2018), the Sentiment Analysis shared task was the first evaluation campaign for the Vietnamese lan-guage. In this paper, we describe our system for this shared task. We employ a supervised learningmethod based on the Support Vector Machine classifiers combined with a variety of features. Weobtained the F1-score of 61% for both domains, which was ranked highest in the shared task. For theaspect detection subtask, our method achieved 77% and 69% in F1-score for the restaurant domainand the hotel domain respectively.
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A transformation method for aspect-based sentiment analysis / Đặng Văn Thìn...
// Tạp chí Tin học và Điều khiển học Vol.34, No 4 2018.tr.323-333 Along with the explosion of user reviews on the Internet, sentiment analysis has becomeone of the trending research topics in the field of natural language processing. In the last five years,many shared tasks were organized to keep track of the progress of sentiment analysis for various lan-guages. In the Fifth International Workshop on Vietnamese Language and Speech Processing (VLSP2018), the Sentiment Analysis shared task was the first evaluation campaign for the Vietnamese lan-guage. In this paper, we describe our system for this shared task. We employ a supervised learningmethod based on the Support Vector Machine classifiers combined with a variety of features. Weobtained the F1-score of 61% for both domains, which was ranked highest in the shared task. For theaspect detection subtask, our method achieved 77% and 69% in F1-score for the restaurant domainand the hotel domain respectively.
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Vlsp shared task : sentiment analysis / Nguyễn Thị Minh Huyền...
// Tạp chí Tin học và Điều khiển học Vol.34, No 4 2018.tr. 295-310 Sentiment analysis is a natural language processing (NLP) task of identifying or
extracting the sentiment content of a text unit. This task has become an active research topic since the early 2000s. During the two last editions of the VLSP workshop series, the shared task on Sentiment Analysis (SA) for Vietnamese has been organized in order to provide an objective evaluation measurement about the performance (quality) of sentiment analysis tools, and encourage
the development of Vietnamese sentiment analysis systems, as well as to provide benchmark datasets for this task. The first campaign in 2016 only focused on the sentiment polarity classication, with a dataset containing reviews of electronic products. The second campaign in 2018 addressed the problem of Aspect Based Sentiment Analysis (ABSA) for Vietnamese, by providing two datasets containing reviews in restaurant and hotel domains. These data are accessible for research purpose via the VLSP website vlsp.org.vn/resources. This paper describes the built datasets as well as the evaluation results of the systems participating to these campaigns.
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话题型微博语言特点及其情感分析策略研究 = Study on the Linguistic Features of the Topic-oriented Microblog and the Strategies for its Sentiment Analysis / 侯敏; 滕永林; 李雪燕; 陈毓麒; 郑双美; 侯明午; 周红照.
// Applied linguistics. 2013, No.2. 2013.135-143 p. Nowadays microblog has become an important way for people to express attitudes,opinions and evaluations.Based on theories about the subjectivity of language,this paper analyzed the linguistic features of topic-oriented microblog texts: short sentences,more negative views,stronger sentiments,weak rationality,more colloquial terms,indirect and obscure way of expressing opinions,ellipsis of evaluated objects,informality,etc.According to the analysis,this paper proposed some strategies for identifying opinion sentence and extracting evaluated object on the basis of phrase emotional dictionary and semantic rules.Experimental evidences and evaluation results proved the effectiveness of these strategies.
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