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DC Field | Value | Language |
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dc.contributor.author | Quan Hoang, Vuong | - |
dc.contributor.author | Viet Phuong, La | - |
dc.contributor.author | Thanh Huyen T, Nguyen | - |
dc.contributor.author | Minh Hoang. Nguyen | |
dc.contributor.author | Tam Tri. Le | |
dc.contributor.author | Manh Toan. Ho | |
dc.date.accessioned | 2022-01-17T02:27:19Z | - |
dc.date.available | 2022-01-17T02:27:19Z | - |
dc.date.issued | 2021 | - |
dc.identifier.uri | https://dlib.phenikaa-uni.edu.vn/handle/PNK/4012 | - |
dc.description | 6(7), 70 | - |
dc.description.abstract | This 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.iso | en | vi |
dc.publisher | MDPI Jourmals | vi |
dc.subject | Online media data | - |
dc.subject | Content Analysis | |
dc.title | An AI-Enabled Approach in Analyzing Media Data: An Example from Data on COVID-19 News Coverage in Vietnam | vi |
dc.type | Bài báo khoa học | vi |
eperson.identifier.doi | https://doi.org/10.3390/data6070070 | - |
Appears in Collections | ||
Bài báo khoa học |
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