Please use this identifier to cite or link to this item: http://cmuir.cmu.ac.th/jspui/handle/6653943832/74731
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dc.contributor.authorXinke Lien_US
dc.contributor.authorPiang Or Loahavilaien_US
dc.contributor.authorNathee Naktnasukanjnen_US
dc.date.accessioned2022-10-16T06:48:37Z-
dc.date.available2022-10-16T06:48:37Z-
dc.date.issued2022-03-25en_US
dc.identifier.other2-s2.0-85134623091en_US
dc.identifier.other10.1145/3532640.3532661en_US
dc.identifier.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85134623091&origin=inwarden_US
dc.identifier.urihttp://cmuir.cmu.ac.th/jspui/handle/6653943832/74731-
dc.description.abstractThe "blockchain + media"model is showing great vitality. In this paper, we study the detection of the most common topics in Steemit. Compared to the currently popular centralized online social media, the blockchain-based decentralized online social media platform presents a different business model, and thus different or platform-specific topics emerge. We extract knowledge from content posted on Steemit, using NLP term frequency and topic modeling techniques combined with sentiment analysis theory, with the aim of studying the topic preferences and sentiment preferences of user-generated content. Our research will provide a more comprehensive understanding of identified themes and detect strategies adopted by users to add value to user-created content; provide guidance for business model improvements; and enrich existing interdisciplinary research.en_US
dc.subjectComputer Scienceen_US
dc.titleA social media platform using blockchain technology: Topic analysis and sentiment analysis of steemit user-generated contenten_US
dc.typeConference Proceedingen_US
article.title.sourcetitleACM International Conference Proceeding Seriesen_US
article.stream.affiliationsChiang Mai Universityen_US
Appears in Collections:CMUL: Journal Articles

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