Int Neurourol J.  2024 Nov;28(Suppl 2):S114-128. 10.5213/inj.2448324.162.

Vasectomy Discussions in South Korea: Central Themes and Public Interest on Question-and-Answer Social Platforms

Affiliations
  • 1General Graduate School, Department of Game Engineering, Gachon University, Seongnam, Korea
  • 2Department of Game Media, College of IT Convergence, Gachon University, Seongnam, Korea

Abstract

Purpose
The purpose of this paper is to explore public perceptions and key issues related to vasectomy in South Korea. In particular, this paper seeks to analyze how vasectomy is discussed on question-and-answer (Q&A) social platforms including NAVER Jisik iN (knowledge exchange service between NAVER users) and to identify topics that capture public interest.
Methods
In this study, based on data collected on NAVER Jisik iN from July 2019 to July 2024 with the keyword ‘vasectomy,’ this paper performs a co-occurrence matrix analysis on the Q&A data to identify key terms related to the topic. By applying connection centrality and community detection techniques, this paper visualizes and examines the network graph to uncover relationships between words and identify the primary topics of discussion.
Results
The co-occurrence matrix analysis reveals that keywords such as ‘surgery,’ ‘vasectomy,’ and ‘contraception’ play a central role in discussions about vasectomies. Both the Q&A data highlight the vasectomy procedure and contraceptive effectiveness as primary topics of discussion. The visualization graphs intuitively display the centrality and strength of connections between these keywords, as well as the interrelatedness of topics through distinct community groups.
Conclusions
The analysis shows that the questions primarily focused on the surgical procedure, while the answers were more concerned with contraceptive effectiveness and physiological aspects. These results suggest that the public’s interest in vasectomy is closely linked to its effectiveness, potential side effects, and related social issues.

Keyword

Vasectomy; Social media; Social network analysis; NAVER Jisik iN, Data analysis; Co-occurrence matrix
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