Análise de comportamento do usuário em redes sociais veiculares
Autor(a) principal: | |
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Data de Publicação: | 2017 |
Tipo de documento: | Dissertação |
Idioma: | por |
Título da fonte: | Repositório Institucional da UFRJ |
Texto Completo: | http://hdl.handle.net/11422/6408 |
Resumo: | Participation in social networks can provide a significant amount of data about users and their surroundings. When properly processed, such data can be used as an important source of information on human behavior if it provides reliable and quality information. In this work, we use a vehicular social network with the main objective of evaluating the impact of external factors on the users present in these environments through their contributions. We can see how speed of user and delay influence the reliability attributed to alerts. It also studies the tendency of improvement or degradation of the reliability attributed to the alerts of each user. It is possible to observe the association between pairs of alerts that occur on the same street in short intervals of time. We verify the interval of consecutive contributions of each user and the ratio of time interval between the first and last contribution and its total number of contributions. Results were obtained through a public dataset of the Waze application, available on the Internet. It was discovered that the most posted alerts are about congestion, and that users mostly do it during peak hours on weekdays and on weekends on the afternoon. It was found that users who move at higher speeds do not contribute to the network, and postings that present the longest delays to be published on the network are poorly evaluated. In addition, there was also a significant association between climate risk alerts and congestion. As the main result, it turned out that users who receive low reliability in their posts tend to keep score low on the following posts. Finally, it was also possible to notice that the interval between the contributions of each user has an average of 10 minutes and are not made daily to the social network, but when they do, the time interval between the alerts has a linear growth. |
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Análise de comportamento do usuário em redes sociais veicularesEngenharia elétricaRedes sociaisRedes veicularesCNPQ::ENGENHARIAS::ENGENHARIA ELETRICAParticipation in social networks can provide a significant amount of data about users and their surroundings. When properly processed, such data can be used as an important source of information on human behavior if it provides reliable and quality information. In this work, we use a vehicular social network with the main objective of evaluating the impact of external factors on the users present in these environments through their contributions. We can see how speed of user and delay influence the reliability attributed to alerts. It also studies the tendency of improvement or degradation of the reliability attributed to the alerts of each user. It is possible to observe the association between pairs of alerts that occur on the same street in short intervals of time. We verify the interval of consecutive contributions of each user and the ratio of time interval between the first and last contribution and its total number of contributions. Results were obtained through a public dataset of the Waze application, available on the Internet. It was discovered that the most posted alerts are about congestion, and that users mostly do it during peak hours on weekdays and on weekends on the afternoon. It was found that users who move at higher speeds do not contribute to the network, and postings that present the longest delays to be published on the network are poorly evaluated. In addition, there was also a significant association between climate risk alerts and congestion. As the main result, it turned out that users who receive low reliability in their posts tend to keep score low on the following posts. Finally, it was also possible to notice that the interval between the contributions of each user has an average of 10 minutes and are not made daily to the social network, but when they do, the time interval between the alerts has a linear growth.A participação em redes sociais pode fornecer significativa quantidade de dados sobre usuários e o ambiente que os cerca. Quando adequadamente processados, esses dados podem ser usados como uma importante fonte de informação sobre o comportamento humano, se oferecerem informações confiáveis e de qualidade. Neste trabalho, usamos uma rede social veicular com o principal objetivo de avaliar o impacto de fatores externos sobre os usuários presentes nesses ambientes através de suas contribuições na rede. Verifica-se como a velocidade do usuário e o atraso da publicação influenciam na confiabilidade atribuída aos alertas. Estuda-se a tendência de melhora ou degradação da confiabilidade de cada usuário. Observa-se a associação entre pares de alerta que ocorrem em uma mesma rua. Verifica-se também o intervalo de contribuições consecutivas de cada usuário e a relação de intervalo de tempo entre sua primeira e a última contribuição. Os resultados foram obtidos através de um conjunto de dados público do aplicativo Waze, disponibilizado na Internet. Foi descoberto que os alertas mais postados são sobre congestionamentos, e que usuários o fazem principalmente nas horas de pico em dias úteis e durante a tarde nos fins de semana. Percebeu-se que os usuários que se movem em velocidades mais elevadas não contribuem para a rede e postagens que apresentam maiores atrasos para serem publicadas na rede são mal avaliadas. Além disso, percebeu-se também significativa associação entre alertas de risco climático e congestionamento. Por fim, foi possível notar que o intervalo entre as contribuições de cada usuário tem uma média de 10 minutos e não são feitas diariamente a rede social, mas quando o fazem, o intervalo de tempo entre os alertas possui um crescimento linear.Universidade Federal do Rio de JaneiroBrasilInstituto Alberto Luiz Coimbra de Pós-Graduação e Pesquisa de EngenhariaPrograma de Pós-Graduação em Engenharia ElétricaUFRJCampista, Miguel Elias Mitrehttp://lattes.cnpq.br/9422341070627584Moraes, Igor MonteiroCosta, Luís Henrique Maciel KosmalskiRibeiro Neto, Victor2019-02-07T16:38:44Z2023-12-21T03:00:49Z2017-06info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesishttp://hdl.handle.net/11422/6408porinfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da UFRJinstname:Universidade Federal do Rio de Janeiro (UFRJ)instacron:UFRJ2023-12-21T03:00:49Zoai:pantheon.ufrj.br:11422/6408Repositório InstitucionalPUBhttp://www.pantheon.ufrj.br/oai/requestpantheon@sibi.ufrj.bropendoar:2023-12-21T03:00:49Repositório Institucional da UFRJ - Universidade Federal do Rio de Janeiro (UFRJ)false |
dc.title.none.fl_str_mv |
Análise de comportamento do usuário em redes sociais veiculares |
title |
Análise de comportamento do usuário em redes sociais veiculares |
spellingShingle |
Análise de comportamento do usuário em redes sociais veiculares Ribeiro Neto, Victor Engenharia elétrica Redes sociais Redes veiculares CNPQ::ENGENHARIAS::ENGENHARIA ELETRICA |
title_short |
Análise de comportamento do usuário em redes sociais veiculares |
title_full |
Análise de comportamento do usuário em redes sociais veiculares |
title_fullStr |
Análise de comportamento do usuário em redes sociais veiculares |
title_full_unstemmed |
Análise de comportamento do usuário em redes sociais veiculares |
title_sort |
Análise de comportamento do usuário em redes sociais veiculares |
author |
Ribeiro Neto, Victor |
author_facet |
Ribeiro Neto, Victor |
author_role |
author |
dc.contributor.none.fl_str_mv |
Campista, Miguel Elias Mitre http://lattes.cnpq.br/9422341070627584 Moraes, Igor Monteiro Costa, Luís Henrique Maciel Kosmalski |
dc.contributor.author.fl_str_mv |
Ribeiro Neto, Victor |
dc.subject.por.fl_str_mv |
Engenharia elétrica Redes sociais Redes veiculares CNPQ::ENGENHARIAS::ENGENHARIA ELETRICA |
topic |
Engenharia elétrica Redes sociais Redes veiculares CNPQ::ENGENHARIAS::ENGENHARIA ELETRICA |
description |
Participation in social networks can provide a significant amount of data about users and their surroundings. When properly processed, such data can be used as an important source of information on human behavior if it provides reliable and quality information. In this work, we use a vehicular social network with the main objective of evaluating the impact of external factors on the users present in these environments through their contributions. We can see how speed of user and delay influence the reliability attributed to alerts. It also studies the tendency of improvement or degradation of the reliability attributed to the alerts of each user. It is possible to observe the association between pairs of alerts that occur on the same street in short intervals of time. We verify the interval of consecutive contributions of each user and the ratio of time interval between the first and last contribution and its total number of contributions. Results were obtained through a public dataset of the Waze application, available on the Internet. It was discovered that the most posted alerts are about congestion, and that users mostly do it during peak hours on weekdays and on weekends on the afternoon. It was found that users who move at higher speeds do not contribute to the network, and postings that present the longest delays to be published on the network are poorly evaluated. In addition, there was also a significant association between climate risk alerts and congestion. As the main result, it turned out that users who receive low reliability in their posts tend to keep score low on the following posts. Finally, it was also possible to notice that the interval between the contributions of each user has an average of 10 minutes and are not made daily to the social network, but when they do, the time interval between the alerts has a linear growth. |
publishDate |
2017 |
dc.date.none.fl_str_mv |
2017-06 2019-02-07T16:38:44Z 2023-12-21T03:00:49Z |
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/11422/6408 |
url |
http://hdl.handle.net/11422/6408 |
dc.language.iso.fl_str_mv |
por |
language |
por |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.publisher.none.fl_str_mv |
Universidade Federal do Rio de Janeiro Brasil Instituto Alberto Luiz Coimbra de Pós-Graduação e Pesquisa de Engenharia Programa de Pós-Graduação em Engenharia Elétrica UFRJ |
publisher.none.fl_str_mv |
Universidade Federal do Rio de Janeiro Brasil Instituto Alberto Luiz Coimbra de Pós-Graduação e Pesquisa de Engenharia Programa de Pós-Graduação em Engenharia Elétrica UFRJ |
dc.source.none.fl_str_mv |
reponame:Repositório Institucional da UFRJ instname:Universidade Federal do Rio de Janeiro (UFRJ) instacron:UFRJ |
instname_str |
Universidade Federal do Rio de Janeiro (UFRJ) |
instacron_str |
UFRJ |
institution |
UFRJ |
reponame_str |
Repositório Institucional da UFRJ |
collection |
Repositório Institucional da UFRJ |
repository.name.fl_str_mv |
Repositório Institucional da UFRJ - Universidade Federal do Rio de Janeiro (UFRJ) |
repository.mail.fl_str_mv |
pantheon@sibi.ufrj.br |
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1815455981698547712 |