Item Infomation


Title: 
An AI-Enabled Approach in Analyzing Media Data: An Example from Data on COVID-19 News Coverage in Vietnam
Authors: 
Quan Hoang, Vuong
Viet Phuong, La
Thanh Huyen T, Nguyen
Minh Hoang. Nguyen
Tam Tri. Le
Manh Toan. Ho
Issue Date: 
2021
Publisher: 
MDPI Jourmals
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.
Description: 
6(7), 70
URI: 
https://dlib.phenikaa-uni.edu.vn/handle/PNK/4012
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