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An AI-enabled approach in analyzing media data: An example from data on COVID-19 news coverage in Vietnam

Vuong Centre for Interdisciplinary Social Research, Phenikaa University, Ha Noi, 100803, Viet Nam|
Manh-Toan (57216039280) | Tam-Tri (57205720535); Ho | Minh-Hoang (57205713877); Le | Thanh-Huyen T. (57216830914); Nguyen | Viet-Phuong (57204013022); Nguyen | Quan-Hoang (45161334600); La AI for Social Data Lab, Vuong & Associates, Ha Noi, 100000, Viet Nam|

Data Số 7, năm 2021 (Tập 6, trang -)

ISSN: 23065729

ISSN: 23065729

DOI: 10.3390/data6070070

Tài liệu thuộc danh mục:

Article

English

Từ khóa: COVID-19; Data visualization; Environmental management; Social networking (online); Web crawler; AI-enabled web crawling; Content analysis; News articles; News coverage; Online medium; Online medium data; Social media datum; Viet Nam; Vietnamese; Web Crawling; Social aspects
Tóm tắt tiếng anh
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. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.

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