Purpose With the rapid development of AI technologies, the problem of multimodal disinformation (MD) has become increasingly serious on social media, posing significant threats to various facets of human society. Although algorithm-based detection could be a solution, human-oriented verification is still crucial in combating online multimodal disinformation. However, there are empirical and theoretical gaps that require attention. Hence, this study investigates human-oriented verification cues and underlying information processing patterns. Design/methodology/approach Guided by the Heuristic-Systematic Model and established information credibility assessment frameworks, we conducted in-depth interviews with 24 social media users for data collection. Subsequently, a hybrid deductive and inductive thematic analysis approach was adopted for qualitative data analysis. Findings We uncovered five key categories of verification cues that were leveraged by individuals, namely (1) modality, (2) content, (3) source, (4) engagement and (5) external. Within these categories, a total of 11 cues were further identified. Additionally, we revealed three information processing patterns underlying the employment of these cues, namely (1) systematic, (2) heuristic and (3) dual-process verification. Generally, our findings show that in social media environments, individuals strategically utilize multiple informational and social cues for MD verification. In this process, dual-process verification is necessary for consolidating judgment-making, enabling the mutual complement between systematic and heuristic cues. Originality/value Distinct from existing research on algorithm-based mitigations, this study adopts a human-oriented perspective. Our proposed categorization of verification cues and patterns serves as a framework for evaluating and validating MD in social media, thereby laying a foundation for further research. Practical implications are also discussed.
Qiu et al. (Tue,) studied this question.