Research Summary: A conceptual framework for ideology in online discourse beyond the left and right

Researchers have introduced a conceptual framework in computational social science that shifts the operationalization of online ideology from a single left-right partisan axis to a multi-level socio-cognitive concept network. The proposed model aims to capture nuanced ideological structures across specific domains—including race, climate, and gender—while clarifying how ideology operates alongside framing and broader value systems.

Why it matters

Relying on binary left-right models obscures the complex ideological structures shaping discourse on critical socioeconomic and environmental matters. Transitioning to multi-level socio-cognitive networks allows analysts and institutions to measure nuanced stakeholder alignments across distinct issues like climate and race. This capability is essential for generating reliable intelligence from digital communications and mitigating analytical blind spots caused by oversimplified political metrics.

Key insights

• Computational social science has historically oversimplified online ideology by mapping discourse onto a single left/right political axis.
• Unidimensional ideological models obscure how individuals interpret and engage with specialized domain-level topics, such as gender, race, and climate.
• The proposed framework models ideology as a multi-level socio-cognitive concept network and connects it directly to computational discourse analysis.
• The framework helps differentiate and connect ideology with adjacent social phenomena, such as framing and multi-concept structures like values.

Source

arXiv — Computers and Society — https://arxiv.org/abs/2603.18945