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dc.contributor.authorQuan Hoang, Vuong-
dc.contributor.authorViet Phuong, La-
dc.contributor.authorThanh Huyen T, Nguyen-
dc.contributor.authorMinh Hoang. Nguyen
dc.contributor.authorTam Tri. Le
dc.contributor.authorManh Toan. Ho
dc.date.accessioned2022-01-17T02:27:19Z-
dc.date.available2022-01-17T02:27:19Z-
dc.date.issued2021-
dc.identifier.urihttps://dlib.phenikaa-uni.edu.vn/handle/PNK/4012-
dc.description6(7), 70-
dc.description.abstractThis method article presents the nuts and bolts of an AI-enabled approach to extracting and analyzing social media data. The method is based on our previous rapidly cited COVID-19 research publication, working on a dataset of more than 14,000 news articles from Vietnamese newspapers, to provide a comprehensive picture of how Vietnam has been responding to this unprecedented pandemic. This same method is behind our IUCN-supported research regarding the social aspects of environmental protection missions, now appearing in print in Wiley’s Corporate Social Responsibility and Environmental Management. Homemade AI-enabled software was the backbone of the study. The software has provided a fast and automatic approach in collecting and analyzing social data. Moreover, the tool also allows manually sorting the data, AI-generated word tokenizing in the Vietnamese language, and powerful visualization. The method hopes to provide an effective but low-cost method for social scientists to gather a massive amount of data and analyze them in a short amount of time.vi
dc.language.isoenvi
dc.publisherMDPI Jourmalsvi
dc.subjectOnline media data-
dc.subjectContent Analysis
dc.titleAn AI-Enabled Approach in Analyzing Media Data: An Example from Data on COVID-19 News Coverage in Vietnamvi
dc.typeBài báo khoa họcvi
eperson.identifier.doihttps://doi.org/10.3390/data6070070-
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Bài báo khoa học

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