The Multidimensional Evolution of Literacy and Its Social Role: An Empirical Study Through Network Analysis
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Purpose: The purpose of this study is to empirically investigate the multidimensional transformation of literacy as a core competency adapting to the digital environment in contemporary society and to propose directions for improving literacy policies and educational programs. Methodology: Using social big data collected from Naver and Daum between 2021 and 2024, the study employed text mining, network analysis, CONCOR analysis, QAP regression, and topic modeling. Key keywords were identified through word frequency and TF-IDF analysis, while N-gram analysis and network visualization were used to examine the relationships between major topics. Findings: The analysis revealed that digital literacy, media literacy, and data literacy emerged as core themes, and their networks demonstrated statistically significant structural patterns. QAP regression analysis confirmed that the literacy-related network exhibited clear patterns compared to a random network, and CONCOR analysis indicated that major topics were closely interconnected. Implication: Policy recommendations include collaborating with community stakeholders to develop localized literacy programs, enhancing digital infrastructure to reduce the information gap, and offering lifelong learning opportunities. Subsidized digital literacy workshops can help address disparities in underserved areas. Integrated approaches in policy and education are essential, with tailored programs and policy support to reduce information inequality.
Abstract
Purpose: The purpose of this study is to empirically investigate the multidimensional transformation of literacy as a core competency adapting to the digital environment in contemporary society and to propose directions for improving literacy policies and educational programs. Methodology: Using social big data collected from Naver and Daum between 2021 and 2024, the study employed text mining, network analysis, CONCOR analysis, QAP regression, and topic modeling. Key keywords were identified through word frequency and TF-IDF analysis, while N-gram analysis and network visualization were used to examine the relationships between major topics. Findings: The analysis revealed that digital literacy, media literacy, and data literacy emerged as core themes, and their networks demonstrated statistically significant structural patterns. QAP regression analysis confirmed that the literacy-related network exhibited clear patterns compared to a random network, and CONCOR analysis indicated that major topics were closely interconnected. Implication: Policy recommendations include collaborating with community stakeholders to develop localized literacy programs, enhancing digital infrastructure to reduce the information gap, and offering lifelong learning opportunities. Subsidized digital literacy workshops can help address disparities in underserved areas. Integrated approaches in policy and education are essential, with tailored programs and policy support to reduce information inequality.