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Sentiment Classification of Drug Reviews Using a Rule-Based Linguistic Approach

机译：利用基于规则的语言方式对药物评论的情感分类

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摘要

Clause-level sentiment classification algorithm is developed and applied to drug reviews on a discussion forum. The algorithm adopts a pure linguistic approach of computing the sentiment of a clause from the prior sentiment scores assigned to individual words, taking into consideration the grammatical dependency structure of the clause using the sentiment analysis rules. MetaMap, a medical resource tool, is used to identify various disease terms in the review documents to utilize domain knowledge for sentiment classification. Experiment results with 1,000 clauses show the effectiveness of the proposed approach, and it performed significantly better than baseline machine learning approaches. Various challenging issues were identified through error analysis, and we will continue improving our linguistic algorithm.
机译：条款级情绪分类算法开发并应用于讨论论坛的药物评论。该算法采用了从分配给单个单词的先前情绪分数计算子句情绪的纯语言方法，考虑了使用情感分析规则的子句的语法依赖结构。 Metamap是一种医疗资源工具，用于识别审查文件中的各种疾病术语，以利用域名知识进行情绪分类。实验结果与1,000个条款表明了所提出的方法的有效性，它比基线机器学习方法明显更好。通过错误分析确定了各种具有挑战性的问题，我们将继续提高我们的语言算法。

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