5G Service and Discourses on Hyper-connected Society in South Korea: Text Mining of Online News

Xu, Li; Yeo, Harim; Hwang, Hyunsang; Kim, Kee Ok

doi:10.1007/978-3-030-39442-4_68

Cited by 3 publications

(1 citation statement)

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“…They used LDA to group words in topics. Also, [6] used LDA and network analysis to explore social media discourse on hyper-connected society base on news articles [6].…”

Section: Introductionmentioning

confidence: 99%

Topic identification from news blog in Spanish language

Pacheco-Guevara¹,

Reátegui²,

Valdiviezo-Díaz³

2022

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Currently exist a large amount of news in a digital format that need to be classified or labeled automatically according to their content. LDA is an unsupervised technique that automatically creates topics based on words in documents. The present work aims to apply LDA in order to analyze and extract topic from digital news in Spanish language. A total of 198 digital news was collected from a university news blog. A data pre-processing and representation in vector spaces was carried out and k values were selected based on coherence metric. A TF_IDF matrix and a combination of unigrams and bigrams produce topics with a variety of terms and topics related to university activities like study programs, research, projects for innovation and social responsibility. Furthermore, with the manual validation process, terms in topics correspond with hashtags written by the communication professionals.

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“…They used LDA to group words in topics. Also, [6] used LDA and network analysis to explore social media discourse on hyper-connected society base on news articles [6].…”

Section: Introductionmentioning

confidence: 99%

Topic identification from news blog in Spanish language

Pacheco-Guevara¹,

Reátegui²,

Valdiviezo-Díaz³

2022

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5G Based Autonomous Vehicle Issue Analysis: Text Mining South Korean News Data

Choi

Yoo

et al. 2023

Lecture Notes in Networks and Systems

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Text Mining of Online News, Social Media, and Consumer Review on Artificial Intelligence Service

Xu¹,

Lim²,

Yeo³

et al. 2021

Fam. Environ. Res

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This study looked through the text mining analysis to check the status of the virtual assistant service, and explore the needs of consumers, and present consumer-oriented directions. Trendup 4.0 was used to analyze the keywords of AI services in Online News and social media from 2016 to 2020. The R program was used to collect consumer comment data and implement Topic Modeling analysis. According to the analysis, the number of mentions of AI services in mass media and social media has steadily increased. The Sentimental Analysis showed consumers were feeling positive about AI services in terms of useful and convenient functional and emotional aspects such as pleasure and interest. However, consumers were also experiencing complexity and difficulty with AI services and had concerns and fears about the use of AI services in the early stages of their introduction. The results of the consumer review analysis showed that there were topics(Technical Requirements) related to technology and the access process for the AI services to be provided, and topics (Consumer Request) expressed negative feelings about AI services, and topics(Consumer Life Support Area) about specific functions in the use of AI services. Text mining analysis enable this study to confirm consumer expectations or concerns about AI service, and to examine areas of service support that consumers experienced. The review data on each platform also revealed that the potential needs of consumers could be met by expanding the scope of support services and applying platform-specific strengths to provide differentiated services.

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5G Service and Discourses on Hyper-connected Society in South Korea: Text Mining of Online News

Cited by 3 publications

References 1 publication

Topic identification from news blog in Spanish language

Topic identification from news blog in Spanish language

5G Based Autonomous Vehicle Issue Analysis: Text Mining South Korean News Data

Text Mining of Online News, Social Media, and Consumer Review on Artificial Intelligence Service

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