Leveraging newly available big data for urban architectural heritage: designing a recommendation system for heritage sites through the lens of social media

Sevim Sezi Karayazı, Gamze Z. Dane, Bauke de Vries

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Abstract

Urban heritage sites are essential part of the cities, because they reflect the historical background of societies and create attraction for tourism industry. However, as tourism industry focuses exclusively on economic growth, usually historical urban cores are under the pressure of mass tourism and urbanization, causing negative experiences for residents and visitors such as overcrowd, nuisance and waste. Therefore, there is a need to understand what attributes attract visitors to certain heritage sites and which heritage sites are overrepresented in space and time, so that recommendations can be given to the visitors and local government in order to reduce the negative impacts of mass tourism. On the other hand, the rise of Internet usage has fundamentally changed the perception for built environment. People are able to reflect own ideas or opinions leaving behind their digital footprints within urban areas. Such digital footprints can be collected as datasets that reflect people’s behaviors and opinion in time and space. In this respect, the aim of this paper is to define a common framework for extracting information on the attractiveness and representation of heritage sites by using spatial big data. This paper reports a conceptual framework in order to investigate the motivations of visitors to visit the heritage sites and the influences of their visitations to the heritage sites by exploiting spatial big data and analytics. Moreover, a bibliometric network among the keywords related to existing state-of-the-art is revealed in the literature review section by using VOSviewer. The paper will conclude with discussions on how the results of the proposed framework can contribute to designing positive tourist experiences in overly touristic historical cities. Furthermore, Destination Management Organizations (DMO’s) can benefit from the results of this proposed framework since they can develop urban facilities in more peripheral areas instead of heavily touristified zones.
Original languageEnglish
Title of host publicationProceedings of 25th International Conference on Urban Planning and Regional Development in the Information Society GeoMultimedia 2020
Pages553-563
ISBN (Electronic)978-3-9504173-8-8
Publication statusPublished - 2020
Event25th International Conference on Urban Planning and Regional Development in the Information Society GeoMultimedia 2020 - Aachen, Germany
Duration: 15 Sept 202018 Sept 2020
https://eura.org/25th-international-conference-on-urban-planning-and-regional-development-in-the-information-society-geomultimedia-2020/

Conference

Conference25th International Conference on Urban Planning and Regional Development in the Information Society GeoMultimedia 2020
Country/TerritoryGermany
CityAachen
Period15/09/2018/09/20
Internet address

Keywords

  • urban heritage
  • overtourism
  • crowdsourcing
  • big data
  • context-aware recommendation

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