Publicação
Community Safety and Well-being in Touristic Spots Using Open Data
| dc.contributor.author | Assis, Dineu | |
| dc.contributor.author | Neto, Miguel de Castro | |
| dc.contributor.author | Motta, Marcel | |
| dc.contributor.institution | NOVA Information Management School (NOVA IMS) | |
| dc.contributor.institution | Information Management Research Center (MagIC) - NOVA Information Management School | |
| dc.date.accessioned | 2021-01-21T23:46:12Z | |
| dc.date.available | 2021-01-21T23:46:12Z | |
| dc.date.issued | 2021-02 | |
| dc.description | Assis, D., De Castro Neto, M., & Motta, M. (2021). Community Safety and Well-being in Touristic Spots Using Open Data. International Journal of Modeling and Optimization, 11(1), 1-11. https://doi.org/10.7763/IJMO.2021.V11.770 | |
| dc.description.abstract | There are many different reasons that can lead a tourist to decide which destination will be chosen on his/her next trip. Besides knowing what are the attractions that must be visited, it is also common to look for more information regarding the overall safety and well-being conditions of travel destinations. Usually shared by local authorities, this kind of information can also be found in a less structured form through public sources, such as web sites and social platforms. However, there are a couple of challenges to be considered: the predominance of unstructured data; the lack of a common standard to distinguish safe and unsafe places; the distinct period needed to update the collected data. In this study, the proposed model combines official census data with open data, social platforms and other online sources, allowing the definition of a score for touristic spots in Lisbon. The resulting score should be able to quantify the community safety and well-being, as well as to identify threats and opportunities for the local tourism industry. Furthermore, it would not only help tourists in their traveling decisions but also, allow decision-makers to track socioeconomic issues and to support public management through a data-driven approach. | en |
| dc.description.version | publishersversion | |
| dc.description.version | published | |
| dc.format.extent | 11 | |
| dc.format.extent | 1036690 | |
| dc.identifier.doi | 10.7763/IJMO.2021.V11.770 | |
| dc.identifier.issn | 2010-3697 | |
| dc.identifier.other | PURE: 27620567 | |
| dc.identifier.other | PURE UUID: 1bc465b8-7b4d-4374-a67a-5fc04ff1d051 | |
| dc.identifier.other | crossref: 10.7763/IJMO.2021.V11.770 | |
| dc.identifier.other | ORCID: /0000-0002-7265-3890/work/87261965 | |
| dc.identifier.uri | http://hdl.handle.net/10362/110540 | |
| dc.identifier.url | http://www.ijmo.org/index.php?m=content&c=index&a=show&catid=107&id=974 | |
| dc.language.iso | eng | |
| dc.peerreviewed | yes | |
| dc.subject | Community safety | |
| dc.subject | Well-being | |
| dc.subject | Tourism | |
| dc.subject | Smart cities | |
| dc.subject | Urban analytics | |
| dc.subject | Data mining | |
| dc.subject | SDG 11 - Sustainable Cities and Communities | |
| dc.title | Community Safety and Well-being in Touristic Spots Using Open Data | en |
| dc.type | journal article | |
| degois.publication.firstPage | 1 | |
| degois.publication.issue | 1 | |
| degois.publication.lastPage | 11 | |
| degois.publication.title | International Journal of Modeling and Optimization | |
| degois.publication.volume | 11 | |
| dspace.entity.type | Publication | |
| rcaap.rights | openAccess |
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