关键词: 错误信息, 信号检测论, 影响因素, 系统2动机性推理理论, 经典推理理论

Abstract: While the evolution of internet communication technologies has brought numerous conveniences, it has also fostered certain hazards, among which misinformation stands prominent. Numerous studies and theories have unraveled the determinants that influence individuals' ability to identify information. This paper highlights two significant accounts that inform our understanding of misinformation identification: motivated System 2 reasoning account and classical reasoning account. Some studies consider the two theories as opposing viewpoints, which is a misunderstanding. This confusion may stem from the imprecise correlation between the theoretical constructs and the measurement tools used in research, as well as a tendency to view factors from different categories as contradictory. At the core, the issue lies in the insufficient differentiation of the impact of various factors on misinformation identification.
Adopting a signal detection theory, this paper categorizes the influencing factors of misinformation identification into two pathways: those affecting discrimination sensitivity and those affecting judgment criterion. This approach allows researchers to understand more clearly and deeply the role different factors play in misinformation identification, reconciling existing theoretical discrepancies. Additionally, the paper integrates factors of emotions and information characteristics into the model. The impact of emotions on misinformation identification is twofold: they can influence judgment criterion by strengthening or suppressing individual stances; they can also decrease individuals' discrimination sensitivity by competing with rational thought processes, thereby affecting misinformation identification. Information characteristics serve as cues and bases for misinformation identification, thus affecting individuals' discrimination sensitivity. The smaller the feature difference between misinformation and true information, the lower individuals' discrimination sensitivity, making it harder to distinguish between the two. Conversely, larger feature differences enhance individuals' discrimination sensitivity, facilitating the differentiation of misinformation from true information. Moreover, the paper delves into the deep-seated causes of partisan bias, expanding this specific example into a broader stance applicable across different scenarios and cultural contexts. Specifically, partisan stances merely represent the superficial manifestations affecting judgment criterion, while the underlying motives, such as actual interests and psychological needs behind these stances, are the core elements influencing judgment criterion. By augmenting and refining the hierarchical model of misinformation identification based on signal detection theory, this paper provides a more comprehensive theoretical framework for researchers to understand how individuals identify misinformation, also offering theoretical support for the practical application of information identification and governance.

Key words: misinformation, signal detection theory, affecting factors, motivated System 2 reasoning account, classical reasoning account