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Destination image (DI) has an important role in destination choice. DI is considered as one of the main factors in destination competitiveness. The main aim of this study was to explore the projected image of Portugal as a tourism destination. The projected image was obtained through an analysis of the pictures of the official page of destination management organization of Portugal on Instagram (@visitportugal). The research used a sample of 1,306 photos. Samples included photographic and textual data. Visual content analysis and content analysis were adopted to analysis data. Appling content analysis for images refers to break a picture into a number of categories. The results showed that the projected destination images of Portugal were dominated by attributes related to natural attractions. In addition, the geographical distribution of the DMO photos showed that 880 photos (67%) of all 1,306 DMO photos were associated with nine destinations. Food/drink category was the most engaging image for followers. Additionally, the findings indicated that the most common applied hashtags for describing Portugal as a tourism destination and inspire travelers to visit were related to nature-based activities (e.g., nature, river, beach, ocean, sea).

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User-generated review of hotels plays an important role in the e-commerce and big data era. The digital and big data era has created novel sources of information that can be used by scholars for knowledge creation, business intelligence, and bringing meaning into unstructured big data. In addition to build a big picture on sources of satisfaction and dissatisfaction, this study aims to develop results that are more practical for hoteliers. A text-mining approach was applied. Reviews of 10 hotels were collected from TripAdvisor.com for Mazandaran province in Iran. The findings of the research show that "location" appearing 99 times, "room" 53 times, and "staff" and "restaurant" 40 times are the most influential factors that determine positive reviews (customer satisfaction). At the same time, the main determinants of customer dissatisfaction were the words "restaurant," "Wi-Fi," and again "room." Given these results, it can be said that customer satisfaction and dissatisfaction can coexist, as literature shows. In this respect, the factors (e.g., room & restaurant) that make customers satisfied have potential to also make them dissatisfied, if they are not provided and properly delivered. Managerial implications are also discussed.