Site Selection Using Geo-Social Media: A Study For Eateries In Lisbon

Detalhes bibliográficos
Autor(a) principal: Puri, Jaskaran Singh
Data de Publicação: 2023
Tipo de documento: Dissertação
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10362/150970
Resumo: Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies
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spelling Site Selection Using Geo-Social Media: A Study For Eateries In LisbonSite SelectionGeographic Self-Organizing MapsGeospatial AnalysisRetailSocial MediaDissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial TechnologiesThe rise in the influx of multicultural societies, studentification, and overall population growth has positively impacted the local economy of eateries in Lisbon, Portugal. However, this has also increased retail competition, especially in tourism. The overall increase in multicultural societies has also led to an increase in multiple smaller hotspots of human-urban attraction, making the concept of just one downtown in the city a little vague. These transformations of urban cities pose a big challenge for upcoming retail and eateries store owners in finding the most optimal location to set up their shops. An optimal site selection strategy should recommend new locations that can maximize the revenues of a business. Unfortunately, with dynamically changing human-urban interactions, traditional methods like relying on census data or surveys to understand neighborhoods and their impact on businesses are no more reliable or scalable. This study aims to address this gap by using geo-social data extracted from social media platforms like Twitter, Flickr, Instagram, and Google Maps, which then acts as a proxy to the real population. Seven variables are engineered at a neighborhood level using this data: business interest, age, gender, spatial competition, spatial proximity to stores, homogeneous neighborhoods, and percentage of the native population. A Random Forest based binary classification method is then used to predict whether a Point of Interest (POI) can be a part of any neighborhood n. The results show that using only these 7 variables, an F1-Score of 83% can be achieved in classifying whether a neighborhood is good for an “eateries” POI. The methodology used in this research is made to work with open data and be generic and reproducible to any city worldwide.Painho, Marco Octávio TrindadeTang, Vicente de AzevedoCasteley, SvenRUNPuri, Jaskaran Singh2023-03-21T19:34:47Z2023-03-012023-03-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10362/150970TID:203254473enginfo: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:RCAAP2024-03-11T05:33:24Zoai:run.unl.pt:10362/150970Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:54:23.672103Repositório 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 Site Selection Using Geo-Social Media: A Study For Eateries In Lisbon
title Site Selection Using Geo-Social Media: A Study For Eateries In Lisbon
spellingShingle Site Selection Using Geo-Social Media: A Study For Eateries In Lisbon
Puri, Jaskaran Singh
Site Selection
Geographic Self-Organizing Maps
Geospatial Analysis
Retail
Social Media
title_short Site Selection Using Geo-Social Media: A Study For Eateries In Lisbon
title_full Site Selection Using Geo-Social Media: A Study For Eateries In Lisbon
title_fullStr Site Selection Using Geo-Social Media: A Study For Eateries In Lisbon
title_full_unstemmed Site Selection Using Geo-Social Media: A Study For Eateries In Lisbon
title_sort Site Selection Using Geo-Social Media: A Study For Eateries In Lisbon
author Puri, Jaskaran Singh
author_facet Puri, Jaskaran Singh
author_role author
dc.contributor.none.fl_str_mv Painho, Marco Octávio Trindade
Tang, Vicente de Azevedo
Casteley, Sven
RUN
dc.contributor.author.fl_str_mv Puri, Jaskaran Singh
dc.subject.por.fl_str_mv Site Selection
Geographic Self-Organizing Maps
Geospatial Analysis
Retail
Social Media
topic Site Selection
Geographic Self-Organizing Maps
Geospatial Analysis
Retail
Social Media
description Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies
publishDate 2023
dc.date.none.fl_str_mv 2023-03-21T19:34:47Z
2023-03-01
2023-03-01T00:00:00Z
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/10362/150970
TID:203254473
url http://hdl.handle.net/10362/150970
identifier_str_mv TID:203254473
dc.language.iso.fl_str_mv eng
language eng
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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
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