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This study describes the visualization of customer expectations using the service science domain. Customer expectations influence service quality and are considered important factors for user evaluation of services. Customer expectations are constructed from word of mouth, rumors, and user experience. Investigation using a questionnaire is useful in comprehending customer expectations, but this method is costly and time consuming. In this research, we extract customer expectations from Web text consisting of massive wordof-mouth data and visualize them using a co-occurrence graph. In addition, we apply clustering and autolabeling methods to easily understand the results of the co-occurrence graph. In the case study of a coffee service, we are able extract topics related to customer expectations, but labeling methods are still subject to

Visualization of Customer Expectations from Web Text using Co-Occurrence Graph and Auto-labeling in the Service Market