Identify popular hotspots through the analysis of movement patterns from social networks in rural areas: Case study of the Borbera Valley in North Italy
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Tipo de documento: | Dissertação |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10362/135045 |
Resumo: | Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies |
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Identify popular hotspots through the analysis of movement patterns from social networks in rural areas: Case study of the Borbera Valley in North Italysocial mediassocial medias scrapingInstagramnetwork analysisSklearnGEPHIDissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial TechnologiesSocial networks are now an increasingly used tool, but analysis possibilities have not yet been fully exploited. In particular, the extraction of information from users' profiles and their processing could give different information. In this work we will focus on the possibilities of using this information to analyse the patterns of rural spaces. The work will be carried out through a review of the available bibliography on the topic, the construction of an application, and the subsequent analysis of the data extracted through the application. Based on the findings, suggestions are made about the intensity of people within an area or the changes that have occurred in social activities.Torres Sospedra, JoaquínPinheiro, Flávio Luís PortasRUNCunietti, Stefano2022-03-23T12:19:58Z2022-03-052022-03-05T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10362/135045TID:202970752enginfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-03-11T05:13:30Zoai:run.unl.pt:10362/135045Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:48:17.704409Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Identify popular hotspots through the analysis of movement patterns from social networks in rural areas: Case study of the Borbera Valley in North Italy |
title |
Identify popular hotspots through the analysis of movement patterns from social networks in rural areas: Case study of the Borbera Valley in North Italy |
spellingShingle |
Identify popular hotspots through the analysis of movement patterns from social networks in rural areas: Case study of the Borbera Valley in North Italy Cunietti, Stefano social medias social medias scraping network analysis Sklearn GEPHI |
title_short |
Identify popular hotspots through the analysis of movement patterns from social networks in rural areas: Case study of the Borbera Valley in North Italy |
title_full |
Identify popular hotspots through the analysis of movement patterns from social networks in rural areas: Case study of the Borbera Valley in North Italy |
title_fullStr |
Identify popular hotspots through the analysis of movement patterns from social networks in rural areas: Case study of the Borbera Valley in North Italy |
title_full_unstemmed |
Identify popular hotspots through the analysis of movement patterns from social networks in rural areas: Case study of the Borbera Valley in North Italy |
title_sort |
Identify popular hotspots through the analysis of movement patterns from social networks in rural areas: Case study of the Borbera Valley in North Italy |
author |
Cunietti, Stefano |
author_facet |
Cunietti, Stefano |
author_role |
author |
dc.contributor.none.fl_str_mv |
Torres Sospedra, Joaquín Pinheiro, Flávio Luís Portas RUN |
dc.contributor.author.fl_str_mv |
Cunietti, Stefano |
dc.subject.por.fl_str_mv |
social medias social medias scraping network analysis Sklearn GEPHI |
topic |
social medias social medias scraping network analysis Sklearn GEPHI |
description |
Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022-03-23T12:19:58Z 2022-03-05 2022-03-05T00:00:00Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/masterThesis |
format |
masterThesis |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10362/135045 TID:202970752 |
url |
http://hdl.handle.net/10362/135045 |
identifier_str_mv |
TID:202970752 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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1799138084032348160 |