Earticle

Comparison on the framing of YouTube channels using text mining : Focusing on the issue of "low birth"

원문정보

초록

영어
This study investigates the framing effects of social media videos on users’ perceptions and uncivil behavior related to specific social phenomena. To achieve this, we collected videos posted on YouTube over the past decade with more than 100 comments, focusing on the societal issue of low birth. To compare the framing strategies, we categorized publisher types, conducted a content analysis of emotional triggers in video titles and visual representations in thumbnails, and performed keyword frequency analysis to identify highly recurring words in the titles. We found that each channel types employed distinct emotional framing strategies, and the choice of emotional framing in thumbnails varied significantly depending on the focal subject. The analysis of frequently used words revealed not only the types of words employed in framing but also connections between low birth and other societal issues, such as gender conflict and real estate problems.

목차

Abstract
Introduction
Literature Review
Methods
Data Collection
Content Analysis
Keyword Frequency Analysis
Results
Conclusion
Acknowledgments
References

저자

  • June Yoon [ Sungkyunkwan University, Global Convergence Content Research Center ]
  • Dongwook Kim [ Sungkyunkwan University, Department of Applied Data Science ]
  • Hwijoo Lee [ Sungkyunkwan University, Department of Applied Data Science ]
  • Eojin Lim [ Sungkyunkwan University, Department of Applied Data Science ]

참고문헌

자료제공 : 네이버학술정보

    간행물 정보

    • 간행물
      한국경영정보학회 정기 학술대회 [KMIS Conference]
    • 간기
      반년간
    • 수록기간
      1990~2025
    • 십진분류
      KDC 325 DDC 658