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.

Highlights

  • User-generated content is rapidly being recognized as a complementary source of data for traditional spatial datasets [1]

  • 63% of all respondents answered the questions about social media usage

  • We found no significant difference between the 3.d6i.sWtrihbouAtiorenthoef Vfriesqituoresn?cies of surveyed home locations and potential home locations observed from social media (χ2 = 190, df = 180, p-value = 0.2903)

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Summary

Introduction

User-generated content is rapidly being recognized as a complementary source of data for traditional spatial datasets [1]. Among other forms of user-generated geographic information, location-based social media provide constant feeds of content-rich data generated by users of different platforms sharing their experiences and observations online. These data have the potential to enrich existing data collection methods for mapping spatio-temporal activity patterns and location-based experiences of people. It still needs to be validated whether social media data can be used as a complementary data source for spatial decision making

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