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首页> 外文期刊>International journal on Semantic Web and information systems >Hybrid Approach for Sentiment Analysis of Twitter Posts Using a Dictionary-based Approach and Fuzzy Logic Methods: Study Case on Cloud Service Providers
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Hybrid Approach for Sentiment Analysis of Twitter Posts Using a Dictionary-based Approach and Fuzzy Logic Methods: Study Case on Cloud Service Providers

机译：使用基于字典的方法和模糊逻辑方法的Twitter Posts情感分析的混合方法：云服务提供商研究案例

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摘要

Recently, sentiment analysis of social media has become a hot topic because of the huge amount of information that is provided in these networks. Twitter is a popular social media application offers businesses and government the opportunities to share and acquire information. This article proposes a technique that aims at measuring customers' satisfaction with cloud service providers, based on their tweets. Existing techniques focused on classifying sentimental text as either positive or negative, while the proposed technique classifies the tweets into five categories to provide better information. A hybrid approach of dictionary-based and Fuzzy Inference Process (FIP) is developed for this purpose. This direction was selected for its advantages and flexibility in addressing complex problems, using terms that reflect on human behaviors and experiences. The proposed hybrid-based technique used fuzzy systems in order to accurately identify the sentiment of the input text while addressing the challenges that are facing sentiment analysis using various fuzzy parameters.
机译：最近，由于这些网络中提供的信息大量信息，社交媒体的情感分析已成为一个热门话题。 Twitter是一个受欢迎的社交媒体应用，提供业务和政府分享和获取信息的机会。本文提出了一种基于推文的云服务提供商来衡量客户满意度的技术。现有技术集中在对敏感文本分类为正面或负面，而建议的技术将推文分类为五个类别以提供更好的信息。为此目的开发了一种基于字典和模糊推断过程（FIP）的混合方法。使用反映人类行为和经验的术语，选择了解决复杂问题的优点和灵活性。所提出的基于混合技术使用模糊系统，以便准确地识别输入文本的情绪，同时解决使用各种模糊参数面临情感分析的挑战。

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