Social Media Data Can Be Used to Understand Tourists’ Preferences for Nature‐Based Experiences in Protected Areas

Hausmann, Anna; Toivonen, Tuuli; Slotow, Rob; Tenkanen, Henrikki; Moilanen, Atte; Heikinheimo, Vuokko; Minin, Enrico Di

doi:10.1111/conl.12343

Cited by 312 publications

(273 citation statements)

References 36 publications

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“…Nonetheless, there are still some concerns regarding the use of social media content in this context [47]. These are mainly related to data quality [33], to the posts potential location inaccuracy, to the representativeness of the population using social media [48] and to the possible biased behaviour on social media [49].…”

Section: Research Frameworkmentioning

confidence: 99%

Identifying Tourist Places of Interest Based on Digital Imprints: Towards a Sustainable Smart City

et al. 2017

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Abstract:As cities become increasingly complex, Information and Communication Technologies (ICTs) bring smartness into organisations and communities, contributing to a more competitive tourism destination, i.e., smart tourism destinations. Enhanced information access coupled with a new kind of tourists avid for online content and predisposed to share information on social media, allows for a better understanding of tourist behaviour regarding their spatial distribution in urban destinations. Thus, smart tourism portrays individuals as information makers, refining the available alternatives for tracking their location. Big data analytics is a technology with the potential to develop Smart City services. From the analysis of the spatial distribution of tourists in the city of Lisbon based on data collected from the 'Panoramio' social network, we identify the most popular places in the city in a context of tourist visits. This new data largely contributes to understanding the consumption of space within urban tourist destinations and therefore enables us to differentiate the overcrowded places from the ones with potential to grow. This allows decision-makers to imagine new ways of planning and managing towards a sustainable 'smart' future.

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Section: Research Frameworkmentioning

confidence: 99%

Identifying Tourist Places of Interest Based on Digital Imprints: Towards a Sustainable Smart City

et al. 2017

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“…There are also promising results for utilizing spatio-temporal information of social media posts for visitor monitoring in recreational revenues [10], landscape values [11], and travel patterns [34]. Social media content (text and/or photos) have also been used for mapping cultural ecosystem services [12] and to assess visitors' preferences for biodiversity [35]. Now, there is a need to test to what extent social media content reflects the reported experiences and activities of visitors in different environments and cultural contexts.…”

Section: Introductionmentioning

confidence: 99%

“…The most recent survey was carried out in the area in 2016 including questions about visitors' social media usage. and/or photos) have also been used for mapping cultural ecosystem services [12] and to assess visitors' preferences for biodiversity [35]. Now, there is a need to test to what extent social media content reflects the reported experiences and activities of visitors in different environments and cultural contexts.…”

Section: Introductionmentioning

confidence: 99%

User-Generated Geographic Information for Visitor Monitoring in a National Park: A Comparison of Social Media Data and Visitor Survey

Heikinheimo

Minin

Tenkanen

et al. 2017

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Abstract:Protected area management and marketing require real-time information on visitors' behavior and preferences. Thus far, visitor information has been collected mostly with repeated visitor surveys. A wealth of content-rich geographic data is produced by users of different social media platforms. These data could potentially provide continuous information about people's activities and interactions with the environment at different spatial and temporal scales. In this paper, we compare social media data with traditional survey data in order to map people's activities and preferences using the most popular national park in Finland, Pallas-Yllästunturi National Park, as a case study. We compare systematically collected survey data and the content of geotagged social media data and analyze: (i) where do people go within the park; (ii) what are their activities; (iii) when do people visit the park and if there are temporal patterns in their activities; (iv) who the visitors are; (v) why people visit the national park; and (vi) what complementary information from social media can provide in addition to the results from traditional surveys. The comparison of survey and social media data demonstrated that geotagged social media content provides relevant information about visitors' use of the national park. As social media platforms are a dynamic source of data, they could complement and enrich traditional forms of visitor monitoring by providing more insight on emerging activities, temporal patterns of shared content, and mobility patterns of visitors. Potentially, geotagged social media data could also provide an overview of the spatio-temporal activity patterns in other areas where systematic visitor monitoring is not taking place.

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“…Recreational services can be assessed through monetary [29] or non-monetary evaluations [30]. In particular, non-monetary analyses include approaches based on social media, such as Flickr [31] and Instagram [32], that estimate visitors' preferences in relation to the number of their uploaded geotagged pictures. In our study, R_Val is calculated and mapped through the tool "Visitation: Recreation and Tourism" [33] of the software InVEST that uses data from the social media Flickr; the unit of measure is the "photo-user-day" (PUD) that corresponds to the number of users that took at least one photo in a given spatial unit and day.…”

Section: Definition Of a Taxonomy To Identify A Regional Gimentioning

confidence: 99%

Green Infrastructure and Ecological Corridors: A Regional Study Concerning Sardinia

et al. 2018

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Abstract:We propose a methodological approach to identify a multifunctional green infrastructure (GI) on the basis of four values (conservation value, natural value, recreation value and anthropic heritage) that represent many functions (biodiversity conservation, supply of ecosystem services, recreation, identity building) performed by the landscape. By taking the Italian region of Sardinia as a case study, we argue that the methodology can support the making of landscape plans as understood in the European Landscape Convention. Moreover, we propose and implement a methodology to identify ecological corridors (ECs) connecting Natura 2000 sites (N2Ss), based on the prioritization of functional land patches related to their suitability to ecosystem services delivery, paying particular attention to biodiversity maintenance and enhancement, and taking Sardinia as spatial regional context. The methodology consists of two steps: (i) identifying the most suitable patches to be included in ECs on the basis of their connectivity, that is, on their negative attitude towards contributing to landscape fragmentation; (ii) assessing, through a discrete-choice-model, the suitability of these ECs to be included in a regional GI, starting from the territorial taxonomy based on biodiversity characteristics related to N2Ss, habitat suitability, and recreational and landscape potentials.

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Social Media Data Can Be Used to Understand Tourists’ Preferences for Nature‐Based Experiences in Protected Areas

Cited by 312 publications

References 36 publications

Identifying Tourist Places of Interest Based on Digital Imprints: Towards a Sustainable Smart City

Identifying Tourist Places of Interest Based on Digital Imprints: Towards a Sustainable Smart City

User-Generated Geographic Information for Visitor Monitoring in a National Park: A Comparison of Social Media Data and Visitor Survey

Green Infrastructure and Ecological Corridors: A Regional Study Concerning Sardinia

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