DDI_KEN_2018_VCCR_v01_M_WB Development Economics Data Group 2020-11-20 NADA Version 01 (November 2020) Verification of Crowdsourced Crash Reports Survey 2018 VCCR 2018 KEN_2018_VCCR_v01_M World Bank Group NADA Robert Marty - v01 The purpose of the 2018 Verification of Crowdsourced Crash Reports survey is to physically verify road traffic crash (RTC) reports that were reported by bystanders in Nairobi, Kenya using Twitter/Ma3Route. Ma3Route is a mobile/web/SMS platform that crowdsources transport data and provides users with information on traffic, RTCs, matatu directions and driving reports. Users post RTC or traffic information to Ma3Route, where Ma3Route then publishes the post on Twitter. In this survey, we sought to verify the accuracy of crowdsourced information as a source of RTC data. Kenya Crowdsourced road traffic crash (RTC) reports were verified in Nairobi, Kenya Road traffic crash reports Road traffic crash reports in Nairobi, Kenya -- Sendy Ltd Other [oth] The process by which data for the 2018 Verification of Crowdsourced Crash Reports Survey was collected is decribed below: 1. An algorithm scraped tweets from @Ma3Route in real time and used a machine learning algorithm to detect RTC related tweets. When the algorithm detected a RTC tweet, the tweet was sent to a field coordinator for the project. The field coordinator for the project confirmed whether the tweet reported a crash with sufficient location information and, if so, made a request on the Sendy Ltd platform for a driver to go to the RTC location. Sendy Ltd is a Kenyan on-demand logistics startup that offers a marketplace for deliveries and logistics services using a mobile application that connects clients to motorcycle riders and vehicles. 2. Sendy drivers that were a part of this survey (15 drivers) were alerted of the request. A Sendy driver could choose to accept the request, then would travel to the location. 3. Once a Sendy driver arrived at the RTC location, they filled out a short survey verifying the RTC—if there was no RTC nearby, they were instructed to ask a passer-by if one occurred recently. Sendy drivers were instructed to not go near the crash, and to not interfere with any first responders. Users of the data agree to keep confidential all data contained in these datasets and to make no attempt to identify, trace or contact any individual whose data is included in these datasets. Use of the dataset must be acknowledged using a citation which would include: - the Identification of the Primary Investigator - the title of the survey (including country, acronym and year of implementation) - the survey reference number - the source and date of download Example, World Bank Group. Kenya - Verification of Crowdsourced Crash Reports (VCCR) Survey 2018. Ref. KEN_2018_VCCR_v01_M. Dataset downloaded from [url] on [date]. Licensed access The user of the data acknowledges that the original collector of the data, the authorized distributor of the data, and the relevant funding agency bear no responsibility for use of the data or for interpretations or inferences based upon such uses. crash_verification 73 4 Do you observe a crash at the specified location? Do you observe a crash at the specified location? Do you observe a crash at the specified location? Do you observe a crash at the specified location? Do you observe a crash at the specified location? Do you observe a crash at the specified location? If No, go to next question. 73 No 1 Yes Why is there no crash? Why is there no crash? Why is there no crash? Why is there no crash? Why is there no crash? Why is there no crash? 49 24 1 Crash Cleared 2 Never a Crash 3 Cannot Reach 4 Crash Nearby 5 Other Sysmiss Date/time of tweet (East Africa time) Date/time of tweet (East Africa time) Date/time of tweet (East Africa time) Date/time of tweet (East Africa time) Date/time of tweet (East Africa time) Date/time of tweet (East Africa time) 73 1847793509000 1851412044000 1849372936041.1 Suggested landmark to travel to, provided by algorithm Suggested landmark to travel to, provided by algorithm Suggested landmark to travel to, provided by algorithm Suggested landmark to travel to, provided by algorithm Suggested landmark to travel to, provided by algorithm Suggested landmark to travel to, provided by algorithm 73 NO LANDMARK airport junction airtel allsops alsops avic bangladesh belle vue cabanas capital centre city cabanas commercial foot bridge gari gateway mall general motors gigiri githurai gm gsu hamza hilton garden hilton garden inn imara daima integrity centre james gicuru kangemi kapa karura forest kibera koja roundabout langata libra house mathare hospital mombasa cement muthaiga square muthangari nairobi school outering panari hotel panari sky pangani prison roysambu sabaki sacco safaricom standard stella uchumi uhuru utalii utawala valley