Digital Social Network Modeling for Predicting Interaction and Online Community Solidarity (Journal of Social And Education Research, 2024)
The rapid advancement of digital communication technologies has transformed how individuals interact and build communities online. This study aims to analyze and synthesize previous research on digital social network modeling as a framework for predicting interaction and solidarity within online communities. Using a literature review approach, this research examines studies published between 2012 and 2025 that focus on social network modeling, online interaction analysis, and digital solidarity prediction. The findings reveal that integrating structural data, content, affective factors, and community evolution provides a comprehensive understanding of online social dynamics. Key variables influencing digital solidarity include member engagement, mutual trust, information flow, and the quality of interpersonal relationships. Furthermore, predictive models based on social network analysis (SNA) have proven effective in identifying changes in interaction patterns and assessing the strength of social bonds within digital environments. This study concludes that digital social network modeling serves as an essential tool for strengthening online community management strategies, fostering inclusivity, cohesion, and productivity in the era of Society 5.0.