The study applies the appraisal theory, corpus linguistics, and multimodal critical discourse analysis to identify the positive and negative representation of the Syrian refugees. The researcher collects ten images from Facebook and their comments posted by Europeans, Americans, Australians, and Canadians. The data are collected during 2015, the year in which the Syrian refugee crisis has aggravated, and the flow of the refugees into the western communities has increased. The researcher adopts the appraisal theory of Martin and White (2005) to annotate the attitudinal realizations on UAM CorpusTool 3.0 to highlight the refugees' emotions, behaviour, and conditions. The researcher has used the attitude subsystems: affect, judgement, and appreciation, using the built-in scheme on the software program in addition to other modifications added to get accurate results. The researcher has saved each image comments in a text file which is in turn saved on the software program to be manually annotated. Then the results are automatically retrieved to set a frequency list based on the most representative appraising features displayed by the data. Therefore, the study depends on the quantitative and qualitative analyses. On the visual level, the images are analyzed according to the approach of Machin and Mayr (2012). That is, the multimodal critical discourse analysis of the images enable the researcher to focus on the Syrian refugees' attributes, settings, clothes, facial expressions, salience, gazes, postures, and their interactional strategies with the viewer. The objective is to identify the refugees' identities and ideologies. Hence, the verbal and visual analyses of the data are combined to explore the representation of the Syrian refugees' thoughts, ethics, feelings, and characteristics.