An AI-Enabled Approach in Analyzing Media Data: An Example from Data on COVID-19 News Coverage in Vietnam

• Main Authors: Quan-Hoang Vuong, Viet-Phuong La, Thanh-Huyen T. Nguyen, Minh-Hoang Nguyen, Tam-Tri Le, Manh-Toan Ho
• Format: Article
• Language: English
• Published: MDPI AG 2021-06-01
• Series: Data
• Subjects: online media data; content analysis; AI-enabled web crawling
• Online Access: https://www.mdpi.com/2306-5729/6/7/70

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 <i>Corporate Social Responsibility and Environmental Management</i>. 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.