Internet Gambling through Text Mining Analysis

Authors

  • Junghyun Choi
  • Daeho Seo

DOI:

https://doi.org/10.47750/pnr.2022.13.S03.093

Keywords:

Internet, Gambling, Big Data, Social, Text Mining.

Abstract

The current study aimed to identify the rising phenomenon of online gambling in news data using Big Kinds, and to check the connection structure of important words.This study used the text-mining method to analyze text data collected from the Naver News portal to identify important patternsof Internet gambling. The web-crawling technique was adopted for data collection from January 1, 2020 to December 31, 2021. Since the coronavirus began to spread across Korea in 2020, a two-year time window was established. All news articles within this timeframe containing the keyword “internet gambling” were identified. A total of 1,494 articles were included.The text mining analysis showed that there have been many cases of arrests due to crimes, mainly online gambling, or crimes being committed after the perpetrator became debt-riddendue to online gambling. It can be seen that those who gamble online are mostly linked to crimes. Journalists have brought these topics up in their provocative articles, but the fact that there are no positive articles about online gambling shows that people should be careful about online gambling.Moreover, many articles state that the number of people who enjoyed online gambling has increased significantly as the time spent using the Internet at home increased rapidly due to COVID-19 restrictions. Online gamblers are increasingly having a negative impact on society; however. the government has not formulated any clear measures against this issue. The online gambling industry is expanding, leading to a negative impact on society, and the government needs to take an urgent action.

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Published

2022-09-22

Issue

Section

Articles

How to Cite

Internet Gambling through Text Mining Analysis. (2022). Journal of Pharmaceutical Negative Results, 610-617. https://doi.org/10.47750/pnr.2022.13.S03.093