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Applying Machine Learning and Geolocation Techniques to Social Media Data (Twitter) to Develop a Resource for Urban Planning

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dc.contributor.authorMilusheva, Sveta
dc.contributor.authorMarty, Robert
dc.contributor.authorBedoya, Guadalupe
dc.contributor.authorWilliams, Sarah
dc.contributor.authorResor, Elizabeth
dc.contributor.authorLegovini, Arianna
dc.date.accessioned2020-12-10T15:01:46Z
dc.date.available2020-12-10T15:01:46Z
dc.date.issued2020-12
dc.description.abstractWith all the recent attention focused on big data, it is easy to overlook that basic vital statistics remain difficult to obtain in most of the world. This project set out to test whether an openly available dataset (Twitter) could be transformed into a resource for urban planning and development. The hypothesis is tested by creating road traffic crash location data, which are scarce in most resource-poor environments but essential for addressing the number one cause of mortality for children over age five and young adults. The research project scraped 874,588 traffic-related tweets in Nairobi, Kenya, applied a machine learning model to capture the occurrence of a crash, and developed an improved geoparsing algorithm to identify its location. The project geolocated 32,991 crash reports in Twitter for 2012-20 and clustered them into 22,872 unique crashes to produce one of the first crash maps for Nairobi. A motorcycle delivery service was dispatched in real-time to verify a subset of crashes, showing 92 percent accuracy. Using a spatial clustering algorithm, portions of the road network (less than 1 percent) were identified where 50 percent of the geolocated crashes occurred. Even with limitations in the representativeness of the data, the results can provide urban planners useful information to target road safety improvements where resources are limited.en
dc.identifierhttp://documents.worldbank.org/curated/en/407261607111342557/Applying-Machine-Learning-and-Geolocation-Techniques-to-Social-Media-Data-Twitter-to-Develop-a-Resource-for-Urban-Planning
dc.identifier.doi10.1596/1813-9450-9488
dc.identifier.urihttps://hdl.handle.net/10986/34910
dc.languageEnglish
dc.publisherWorld Bank, Washington, DC
dc.relation.ispartofseriesPolicy Research Working Paper;No. 9488
dc.rightsCC BY 3.0 IGO
dc.rights.holderWorld Bank
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/igo
dc.subjectMACHINE LEARNING
dc.subjectBIG DATA
dc.subjectURBAN PLANNING
dc.subjectROAD SAFETY
dc.subjectSDGs
dc.subjectGEOGRAPHIC INFORMATION SYSTEM
dc.subjectSOCIAL MEDIA
dc.subjectGEOSPATIAL ANALYSIS
dc.subjectSPATIAL CLUSTERING
dc.titleApplying Machine Learning and Geolocation Techniques to Social Media Data (Twitter) to Develop a Resource for Urban Planningen
dc.typeWorking Paperen
dc.typeDocument de travailfr
dc.typeDocumento de trabajoes
dspace.entity.typePublication
okr.crossref.titleApplying Machine Learning and Geolocation Techniques to Social Media Data (Twitter) to Develop a Resource for Urban Planning
okr.date.disclosure2020-12-04
okr.date.doiregistration2025-04-10T11:28:39.174989Z
okr.doctypePublications & Research
okr.doctypePublications & Research::Policy Research Working Paper
okr.docurlhttp://documents.worldbank.org/curated/en/407261607111342557/Applying-Machine-Learning-and-Geolocation-Techniques-to-Social-Media-Data-Twitter-to-Develop-a-Resource-for-Urban-Planning
okr.guid407261607111342557
okr.identifier.doi10.1596/1813-9450-9488
okr.identifier.externaldocumentum090224b0880779ac_1_0
okr.identifier.internaldocumentum32638295
okr.identifier.reportWPS9488
okr.importedtrueen
okr.language.supporteden
okr.pdfurlhttp://documents.worldbank.org/curated/en/407261607111342557/pdf/Applying-Machine-Learning-and-Geolocation-Techniques-to-Social-Media-Data-Twitter-to-Develop-a-Resource-for-Urban-Planning.pdfen
okr.region.administrativeAfrica
okr.region.administrativeAfrica Eastern and Southern (AFE)
okr.region.countryKenya
okr.statistics.combined3548
okr.statistics.dr407261607111342557
okr.statistics.drstats2073
okr.topicTransport::Transport Economics Policy & Planning
okr.topicTransport::Roads & Highways
okr.topicUrban Development::National Urban Development Policies & Strategies
okr.topicUrban Development::Transport in Urban Areas
okr.topicUrban Development::Urban Economic Development
okr.unitDevelopment Impact Evaluation Group, Development Economic
relation.isSeriesOfPublication26e071dc-b0bf-409c-b982-df2970295c87
relation.isSeriesOfPublication.latestForDiscovery26e071dc-b0bf-409c-b982-df2970295c87
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