This paper proposes a unifying conceptual framework for analysing problematic information in order to address persistent terminological fragmentation across disciplines and improve conceptual clarity in research, policy, and practice.
The study synthesises interdisciplinary literature from information science, communication, philosophy, computer science, and policy studies to identify common conceptual gaps. It develops a multidimensional framework structured around three core dimensions, namely, veracity, misleadingness, and harmfulness, complemented by optional contextual attributes such as intent, timeliness, contextuality, provenance, and ambiguity.
The framework demonstrates that many existing terms, including misinformation, disinformation, malinformation, rumours, satire, conspiracy theories, and deepfakes, can be more precisely characterised through explicit dimensional combinations rather than fixed categorical labels. This approach clarifies conceptual boundaries, explains overlaps and disagreements in prior definitions, and provides a systematic method for generating consistent terminology across analytical contexts. The framework also highlights how different dimensions become salient in tasks such as detection, moderation, fact-checking, and regulation.
Unlike prior typologies that emphasise single criteria such as falsity or intent, this framework introduces a structured, extensible dimensional model that separates core properties of information from context-dependent attributes. It contributes a generalisable conceptual architecture designed to support interdisciplinary research and improve definitional precision in the study of problematic information.
