利用双向长短期记忆检测推特中对印度的负面情绪的情感分析实现

Muhammad Kemal Hernandi, S. Wibowo, S. Suyanto
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引用次数: 1

摘要

情感分析是从用人类语言写的文本中提取观点的方法。情感分析可用于分析和评估所提供服务的客户体验。随着社交媒体的便捷接入,情感分析可以从人们在社交媒体上的评论中应用。适合进行情感分析的社交媒体之一是Twitter。在本文中,我们专注于使用印度消费者在Twitter上的推文进行负面情绪检测。该系统采用BiLSTM方法进行情感分析。使用BiLSTM,准确率达到88%。
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Sentiment Analysis Implementation For Detecting Negative Sentiment Towards Indihome In Twitter Using Bidirectional Long Short Term Memory
Sentiment analysis is the method of extracting opinions from texts written in human language. Sentiment analysis can be used to analyze and evaluate the customer experience of the services that have been provided. With easy access to social media, sentiment analysis can be applied from people's comments on social media. One of the social media that is suitable for sentiment analysis is Twitter. In this paper, we focus on negative sentiment detection using tweets on Twitter by Indihome consumers. The system is designed to apply sentiment analysis using the BiLSTM method. Using BiLSTM, the accuracy 88 % is achieved.
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