Digital Citizenship dalam Memitigasi Fractured Reality dan Polarisasi Informasi pada Ekosistem Algoritma Digital
DOI:
https://doi.org/10.47200/aossagcj.v6i1.3576Keywords:
digital citizenship, fractured reality, ekosistem algoritma digital, polarisasi informasi, algorithmic literacyAbstract
The development of the digital algorithm ecosystem (DAE) creates an epistemological risk in the form of fractured reality (FR), namely a condition in which society forms different understandings of the same reality due to algorithm-based information curation. This phenomenon strengthens information polarization and threatens the shared factual ground as an important foundation in democracy. This study aims to: (1) analyze the mechanisms of FR formation and information polarization in the DAE; (2) examine the role of digital citizenship (DC) as a mitigation framework; (3) formulate an integrative DC model relevant to the contemporary DAE; and (4) identify pedagogical and policy implications for strengthening digital citizenship. The study uses the systematic literature review (SLR) method with the PRISMA 2020 procedure through searches on Google Scholar, Scopus, and DOAJ. From 74 candidate articles, 23 articles were selected as the main sources of analysis and grouped into three thematic clusters. The results of the study show that FR is formed through three main mechanisms, namely algorithmic content curation, filter bubble formation, and echo chamber amplification. The study also finds that DC, especially in the dimensions of algorithmic literacy, media and information literacy, data literacy, civic engagement online, and digital ethics, plays an important role in building the epistemological resilience of digital citizens. The study concludes that FR mitigation requires layered strategies that operate simultaneously at the individual, community, institutional, and platform levels. The integration of Pancasila values into the global DC framework offers a contextual model for Indonesia and is relevant for other developing countries facing algorithm-based information polarization.
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