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Comparative Analysis of Sentiment Analysis Between All Bigrams and Selective Adverb/Adjective Bigrams

机译:所有双字母组与选择性副词/形容词双字母组的情感分析比较分析

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Increase in the amount of unstructured data across different platforms serves as a valuable resource for predicting market trends, analyzing product features, and considering the customer sentiment in designing new features/products. The sentiment of unstructured data such as tweets, Facebook comments, and web reviews is calculated by using the polarity and intensity of the words, whereas polarity indicates positive or negative sentiment, and intensity indicates the strength of polarity. In this paper, a comparative study of sentiment analysis performance and accuracy between all bigrams and selective adverb/adjective bigrams is done. The outcome of this research will serve as a metric for both academia and industry to implement sentiment analysis projects.
机译:跨不同平台的非结构化数据量的增加可作为预测市场趋势,分析产品功能并在设计新功能/产品时考虑客户情绪的宝贵资源。非结构化数据(例如推文,Facebook评论和Web评论)的情感是通过使用单词的极性和强度来计算的,而极性则表示积极或消极的情感,而强度则表示极性的强弱。本文对所有二元组和选择性副词/形容词二元组之间的情感分析性能和准确性进行了比较研究。这项研究的结果将成为学术界和行业实施情感分析项目的指标。

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