Against the backdrop of high digital uncertainty in the 2023 Thai General Election, this study examines how social media reshapes voting intentions through a novel hybrid framework integrating Fuzzy Rough Set Theory (FRST), Hierarchical Confirmatory Factor Analysis (CFA), and Random Forest Regression (RFR). A three-stage design—combining 23 expert opinions with survey data from 812 voters—overcomes expert ambiguity and non-linear dynamics. The findings reveal a hierarchy in digital campaigning: while Party Image (Importance = 0.3056) is the primary predictor for initial voter attention, substantive Campaign Policy (β = 0.98) remains the definitive driver of final commitment. Other perceptual constructs, including Trust, Loyalty, and Perceived Quality, function as reinforcing dimensions that validate policy claims within the digital ecosystem. This suggests a shift where traditional broadcasting is superseded by interactive digital streaming, allowing voters to scrutinize policies through replays and public comments. The model’s robustness, validated through 10-fold Random Forest Cross-Validation, demonstrates high predictive stability (Mean CV R2 = 0.840) and minimal error (MAE = 0.064). This study offers a sensitive instrument for emerging democracies and provides actionable insights, showing that substantive policy remains the ultimate driver of voter choice, even when mediated through Party Image in interactive digital environments.
Puttamapadungsak et al. (2026) studied this question.