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High volumes of tourists often pose a threat to tourism and decrease the quality of life for local residents, particularly in attractive urban tourism places. Yet, to date only a few solution-oriented studies have attempted to alleviate the overtourism problems and to improve the resident-tourist relationship. This study aims to present potential solutions, based on data analytics. Combining venue-referenced social media data with topic modelling from a case study in Paris, this research reveals both similarities and differences in the temporal and spatial activity patterns of tourists and residents. Results offer strategic support to tourism planners on how to manage over-crowded urban tourism hotspots, which consequently facilitate the improvement of the resident–tourist relationship and improve destination attractiveness in the long run. Results further indicate that the exchange of social media-based information for residents and tourists are part of the practice-based solution for better sustainable tourism planning. [ABSTRACT FROM AUTHOR]

With the prevalence of social media and Web 2.0, online visual contents such as photos or videos have quickly evolved into one popular information-disseminating channel for hotel managers and travelers. The current study aims to obtain a comprehensive understanding of the preconceptions as reflected in online photos posted by travelers. This paper presents a novel approach to online photo content analysis based on deep learning theory and computer vision framework, which can comprehensively analyze the content of large-scale photo datasets. We demonstrate and evaluate this approach through a case study, wherein we analyze over 53,000 photos collected from hotel review platform, TripAdvisor. We identified interesting differences in the contents of photos posted by hotel managers and travelers, including the differences in photo contents between low- and high-rating hotels. Our findings provide valuable implication for hotel marketing using visual assets. [ABSTRACT FROM AUTHOR]

This study introduces topic modelling into the analysis of theme park online reviews to determine visitor behaviour and experiences. An exploratory analysis involving major Disneyland theme parks is presented using a large-scale review data set. A comprehensive list of the topics discussed by visitors when visiting Disneyland theme parks is constructed. Insights into the interests and concerns of various visitor groups across theme parks are revealed. The proposed approach and findings are beneficial to support theme park managers in understanding visitors' perception, through which effective marketing and improvement plans can be developed to attract and retain future customers. [ABSTRACT FROM AUTHOR]

The availability of location-based social media (LBSM) presents various opportunities for tourism researchers and businesses to understand and enhance the traveller experience. However, privacy concerns can prevent users from sharing their location data, impeding the future development of LBSM applications. Privacy issues of LBSM remain under investigation in the tourism literature probably because social media platforms are often assumed to feature good security mechanisms. This paper argues that risks of privacy disclosure exist not from direct access to private data but indirectly through seemingly harmless data published by users. We present a social link mining technique and demonstrate how private and sensitive information in the form of social relationships between travellers can be revealed. The findings can support managers and researchers in realizing the potential privacy risks of LBSM so that effective strategies can be developed to protect users and promote the gains that LBSM can bring. [ABSTRACT FROM AUTHOR]

Zoning is one approach to managing human occurrence and reducing deleterious interactions between humans and wildlife. We investigated the occurrence of humans, and the responses of eight waterbird species to humans, at a major wetland/treatment plant/birdwatching destination. Human occurrence in three zones ('open birdwatching', 'limited birdwatching' and 'restricted access') was monitored using GPS tracking of visitor vehicles, surveys, geotagged social media uploads and remotely triggered cameras (on primary and secondary roadways). A higher diversity (but not frequency) of vehicle types and more walkers, more social media uploads, and greater usage occurred in zones in which birdwatching was permitted. Vehicles were less common and diverse on secondary roads, suggesting accessibility influenced human occurrence. Bird responsiveness to humans was similar across zones, perhaps because people were ubiquitous or because birds were mobile. Wildlife disturbance studies which use space-experience substitution designs are cautioned to test their assumptions regarding patterns of human visitation. [ABSTRACT FROM AUTHOR]

This research introduces the use of venue check-ins, which are available on mobile social media platforms, as an additional data source to study tourist behaviors in gaming destinations. The practical value of venue check-ins is demonstrated through a case study of Macau, a popular gaming and cultural destination. The analyses provide an overview of the travel patterns of tourists to gambling and non-gambling venues and highlight the differences between gambling and non-gambling tourists. The introduced approach is beneficial to tourism managers in understanding tourist behaviors and interests and, thus, improves the management and development of gaming destinations. [ABSTRACT FROM AUTHOR]

Identification of hotel competitiveness is crucial for hotel managers in developing effective marketing strategies and promoting their business. A common practice in representing hotel competitiveness is to advertise hotel features with high customer ratings as selling points. However, this approach is ineffective to clearly distinguish top-tier hotels with similar high ratings, while low-tier hotels are disadvantaged because of their low ratings. This study presents a new approach for hotel competitiveness evaluation by identifying the unique aspects that combine multiple features. The proposed approach could distinguish a hotel from its counterparts, rather than rely solely on the high ratings of hotel features. We introduce a data mining technique to automatically discover the distinct aspects of a hotel based on the ratings of hotel features. The proposed method is beneficial to researchers and hotel managers in evaluating hotel competitiveness and identifying critical features that need improvement to considerably attract potential customers. [ABSTRACT FROM AUTHOR]

This research introduces online travel photos published on social media platforms as a complementary data resource to examine the behavior and experience of museum visitors. The practical value of online travel photos is demonstrated through a case study of popular Hong Kong museums, particularly by using the photo content and metadata available from the Flickr platform. The proposed approach is a generic method for understanding museum visitor behavior and preferences, and supports museum practitioners in developing improved products for visitors. The case study findings are particularly beneficial for tourism managers, especially those in Hong Kong, in promoting and attracting tourists to visit local museums. [ABSTRACT FROM AUTHOR]

Variations between journal rankings may cause confusion. As such, prior attempts were made to compare and evaluate journal ranking criteria for obtaining insightful knowledge on how different research communities have ranked journals. However, existing approaches are unable to model the journal ranking process closely enough as they are incapable of considering the relationship between multiple criteria simultaneously. In this paper, we address the challenges by introducing the Choquet Integral (CI) for evaluating journal ranking criteria. The new approach is able to account for interactions between criteria in relation to overall ranking score, using a fuzzy measure in its computation. Its properties, the Shapley value and the Interaction index, allow for good representations of importance and interactions between criteria. We demonstrate the efficiency of the CI through a case study of journal ranking lists in tourism and service journals. [ABSTRACT FROM PUBLISHER]