Identify popular hotspots through the analysis of movement patterns from social networks in rural areas: Case study of the Borbera Valley in North Italy

Detalhes bibliográficos
Autor(a) principal: Cunietti, Stefano
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
id RCAP_c1149bcfc5bd3e1e7279425a8e38e117
oai_identifier_str oai:run.unl.pt:10362/135045
network_acronym_str RCAP
network_name_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository_id_str 7160
spelling 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
Instagram
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
Instagram
network analysis
Sklearn
GEPHI
topic social medias
social medias scraping
Instagram
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
repository.mail.fl_str_mv
_version_ 1799138084032348160

Registros relacionados