Classification of advertisement articles using sentiment analysis: (Research-based on Korean natural language processing and deep learning technology)
Pages 84 - 88
Abstract
We live in a flood of big data and information through computers, communications, social media, and mass media. In other words, we can get the information we want quickly and easily, but we have many questions about the accuracy and reliability of this information. That is, there are many problems in trying to obtain accurate knowledge of such reckless details, and in particular, advertisement articles provided by online newspapers need to be clearer and more manageable when individuals try to find precise information and reports. Such experiences are threatened even to the foundation of existence due to distrust of Internet newspapers and advertisement evasion. To solve this problem, this study used emotion analysis of natural language processing to classify general and advertisement articles. Getting going Existing similar studies have mainly been undertaken to classify such advertisement articles, such as spam mail classification, and most of these studies used general natural language processing. However, this paper is a study that analyzes text data to understand further the meaning of the words, sentences, and phrases and adds steps to explore emotions to provide more accurate information that individuals want.
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Index Terms
- Classification of advertisement articles using sentiment analysis: (Research-based on Korean natural language processing and deep learning technology)
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December 2022
241 pages
ISBN:9781450397629
DOI:10.1145/3582768
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Published: 27 June 2023
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NLPIR 2022
NLPIR 2022: 2022 6th International Conference on Natural Language Processing and Information Retrieval
December 16 - 18, 2022
Bangkok, Thailand
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