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논문검색

Technology Convergence (TC)

A Study on Big Data-Based Analysis of Risk Factors for Depression in Adolescents

원문정보

초록

영어

The purpose of this study is to explore adolescent depression, increase understanding of social problems, and develop prevention and intervention strategies. As a research method, social big data was used to collect information related to 'youth depression', and related factors were identified through data mining and analysis of related rules. We used 'Sometrend Biz Tool' to collect and clean data from the web and then analyzed data in various languages . The study found that online articles about depression decreased during the school holidays (January to March), then increased from March to the end of June, and then decreased again from July. Therefore, it is important to establish a government-wide depression management monitoring system that can detect risk signs of adolescent depression in real time. In addition, regular stress relief and mental health education are needed during the semester , and measures must be prepared to deal with at-risk youth who share their depressed feelings in cyberspace. Results from these studies can be expected to provide important information in investigating and preventing youth depression and to contribute to policy development and intervention.

목차

Abstract
1. INTRODUCTION
2. RESEARCH METHODS
2.1 Research Subject
2.2 Analytics of Big Data
3. ANALYTICS OF BIG DATA
4. RESULTS
5. CONCLUSION
ACKNOWLEDGEMENT
REFERENCES

저자정보

  • Chun-Ok Jang Assistant Professor., Department of Social Welfare, Honam University, Korea

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