Using Twitter to Infer User Satisfaction With Public Transport: The Case of Santiago, Chile

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dc.contributor.authorMéndez Videla, José Tomás
dc.contributor.authorLöbel Díaz, Hans-Albert
dc.contributor.authorParra Santander, Denis
dc.contributor.authorHerrera Maldonado, Juan Carlos
dc.date.accessioned2022-05-18T14:39:50Z
dc.date.available2022-05-18T14:39:50Z
dc.date.issued2019
dc.description.abstractUser satisfaction is an important aspect to consider in any public transport system, and as such, regular and sound measurements of its levels are fundamental. However, typical evaluation schemes involve costly and time-consuming surveys. As a consequence, their frequency is not enough to properly and timely characterize the satisfaction of the users. In this paper, we propose a methodology, based on Twitter data, to capture the satisfaction of a large mass of users of public transport, allowing us to improve the characterization and location of their satisfaction level. We analyzed a massive volume of tweets referring to the public transport system in Santiago, Chile (Transantiago) using text mining techniques, such as sentiment analysis and topic modeling, in order to capture and group bus users' expressions. Results show that, although the level of detail and variety of answers obtained from surveys are higher than the ones obtained by our method, the amount of bus stops and bus services covered by the proposed scheme is larger. Moreover, the proposed methodology can be effectively used to diagnose problems in a timely manner, as it is able to identify and locate trends, and issues related to bus operating firms, whereas surveys tend to produce average answers. Based on the consistency and logic of the results, we argue that the proposed methodology can be used as a valuable complement to surveys, as both present different, but compatible characteristics.
dc.fechaingreso.objetodigital2024-05-17
dc.fuente.origenIEEE
dc.identifier.doi10.1109/ACCESS.2019.2915107
dc.identifier.issn2169-3536
dc.identifier.urihttps://doi.org/10.1109/ACCESS.2019.2915107
dc.identifier.urihttps://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8708245
dc.identifier.urihttps://repositorio.uc.cl/handle/11534/64179
dc.information.autorucEscuela de ingeniería ; Méndez Videla, José Tomás ; S/I ; 204216
dc.information.autorucEscuela de ingeniería ; Lobel Días, Hans Albert ; S/I ; 131278
dc.information.autorucEscuela de ingeniería ; Parra Santander, Denis ; S/I ; 1011554
dc.information.autorucEscuela de ingeniería ; Herrera Maldonado, Juan Carlos ; S/I ; 3146
dc.language.isoen
dc.nota.accesoContenido completo
dc.pagina.final60263
dc.pagina.inicio60255
dc.revistaIEEE Access
dc.rightsacceso abierto
dc.subjectDatabases
dc.subjectTwitter
dc.subjectSentiment analysis
dc.subjectTools
dc.subjectReal-time systems
dc.subjectAnalytical models
dc.subjectSoftware
dc.titleUsing Twitter to Infer User Satisfaction With Public Transport: The Case of Santiago, Chilees_ES
dc.titleUsing Twitter to Infer User Satisfaction With Public Transport: The Case of Santiago, Chile
dc.typeartículo
dc.volumen7
sipa.codpersvinculados204216
sipa.codpersvinculados131278
sipa.codpersvinculados1011554
sipa.codpersvinculados3146
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