PurposeThis study aimed to analyze existing problems in the dissemination and management of emergency information on social media platforms, improve social media users' experience regarding such information, increase the efficiency of emergency information dissemination and curb the spread of misinformation.Design/methodology/approachIn this study, the emergency information quality on social media platforms was examined. Based on the evaluation principles of the quality of mature information, social media information characteristics and the rules of emergency information dissemination, combined with relevant academic research results, an index to evaluate the quality of emergency information on social media was constructed. In addition, the authors have introduced cloud theory as an information quality evaluation method and used social media users' emotional characteristics to assess information quality evaluation results. A comprehensive system for evaluating emergency information quality, including indexes, methods and detection strategies was established. Based on a comprehensive system, a case study was conducted on the forest fires in Sichuan Province and the African swine fever events as reported on the Zhihu platform. In accordance with the results of the case study, the authors expanded the research and introduced the emotional characteristics of social media users as an independent evaluation dimension to evaluate the quality of emergency information on social media.FindingsThe comprehensive system's effectiveness was verified through the case study. Further, it was found that users' emotional characteristics (reflected in their information behavior) are inconsistent with their evaluation of websites' information quality regarding major emergencies. Integrating users' emotional characteristics into the information evaluation system can enhance its effectiveness following major emergencies.Originality/valueFirst, an evaluation index system of emergency information quality on social media about major emergencies was offered. Unlike the commonly available index system for information quality evaluation, this proposed evaluation index system not only accounted for the characteristics of social media, such as massive disordered information, multiple information sources and rapid dissemination, but also for the characteristics of emergency events, such as variability and the absence of precursors. This proposed evaluation index system enhances the pertinence of the information quality evaluation and compensates for the shortcoming that the current research only focuses on evaluating social media information quality in a broad context, but pays insufficient attention to major emergencies. Second, cloud theory was introduced as a method to evaluate the emergency information quality found on social media. Existing research has primarily included the use of traditional statistical methods, which cannot transform numerical values into qualitative concepts effectively. Various indeterminate factors inevitably affect the quality of emergency information on social media platforms, and the traditional methods cannot eliminate this uncertainty in the evaluation process. The method to assess emergency information quality based on cloud theory can effectively compensate for the gaps in the research and improve the accuracy of information quality assessment. Third, the inspection and the dynamic adjustment of assessment results are absent in the research on information quality assessment, and the research has relied principally on the information users' evaluation and has paid insufficient attention to their attitudes and behaviors toward information. Therefore, the authors incorporated users' emotional characteristics into the evaluation of emergency information quality on social media and used them to test the evaluation results so that the results of the information quality assessment not only include the users' explicit attitudes but also their implicit attitudes. This enhances the effectiveness of the information quality assessment system. Finally, through this case study, it was found that an inconsistency exists between user evaluation and user emotional characteristics after major emergencies. The reasons for this phenomenon were explained, and the necessity of integrating user emotional characteristics into information quality assessment was demonstrated. Based on this, the users' emotional characteristics were used as a separate evaluation dimension for assessing the quality of emergency information on social media. Compared with assessing the quality of general information, integrating the user's emotional characteristics into the evaluation index system can lead the evaluation results to include not only the users' cognitive evaluation but also their emotional experience, further enhancing their adaptability.
A Quality of Recognition Case Study: Texture-based Segmentation and MRI Quality Assessment