A Study on the Perception of Abuse Risk among the Elderly using Unstructured Bigdata

비정형 빅데이터를 활용한 고령층 학대 위험성 인식에 관한 연구

(Purpose) This study aims to propose meaningful implications and policy direction by collecting and analyzing major texts related to the risk of abuse of the elderly from media in portal sites. unstructured bigdata analysis using text mining techniques to confirm the risk perception of abuse among the elderly in a situation where external exposure is reduced during COVID-19 was performed. It is meaningful to prepare effective data for follow-up studies related to the prevention of elder abuse and to present the direction of this kind of study. (Design/methodology/approach) To this end, we used Textome, an unstructured big data analysis solution program, to collect keywords related to the risk of abuse among the elderly using portal sites such as Daum, Naver, and Google. The collection period was set from October 2020 to September 2022, and a total of 8,656 keywords were collected, and a total of 60 key keywords were used in this study by refining unnecessary keywords. (Findings) The results of this analysis are as follows. First, as a result of frequency and TF-IDF analysis, keywords were presented in the order of elderly population, abuse prevention, and suspected abuse. Next, as a result of semantic network analysis using Ucinet 6 and NetDraw, both degree and eigenvector centrality were presented in the order of elderly population, elder abuse, abuse prevention, and suspected abuse. Finally, the CONCOR analysis was divided into six groups: cases and types of abuse, phenomena in an aging society, prevention of abuse of the elderly, support law for the prevention of abuse of the elderly, and prevention of abuse of the elderly. (Research Implications or Originality) Through these analysis results, social issues, major attributes, and keywords related to the perception of abuse risk among the elderly were identified. In addition, it is expected to provide meaningful implications for presenting effective data and suggesting a direction for follow-up research related to elder abuse prevention.