Updated
20 December 2021
| Dataset date: July 04, 2021-June 25, 2022
This dataset updates: Every six months
Commuting zones are geographic areas where people live and work and are useful for understanding local economies, as well as how they differ from traditional boundaries. Learn more here: https://dataforgood.facebook.com/dfg/tools/commuting-zones
Updated
15 December 2021
| Dataset date: October 13, 2021-October 13, 2021
This dataset updates: As needed
We use an anonymized snapshot of all active Facebook users and their friendship networks to measure the intensity of connectedness between locations. The Social Connectedness Index (SCI) is a measure of the social connectedness between different geographies. Specifically, it measures the relative probability that two individuals across two locations are friends with each other on Facebook.
Details on the underlying data and the construction of the index are provided in the “Facebook Social Connectedness Index - Data Notes.pdf” file. Please also see https://dataforgood.fb.com/ as well as the associated research paper “Social Connectedness: Measurement, Determinants and Effects,” published in the Journal of Economic Perspectives (https://www.aeaweb.org/articles?id=10.1257/jep.32.3.259).
Region identifiers are taken from GADM v2.8 https://gadm.org/download_country_v2.html. Future versions will update IDs to be compatible with the newest GADM version.
Updated
13 March 2021
| Dataset date: May 01, 2019-February 28, 2021
This dataset updates: Never
This dataset and visualisation show the results of a trial conducted by the Centre for Humanitarian Data and the Artificial Intelligence for Disaster Response (AIDR) project from May 2019 to February 2021, using machine learning to identify Twitter posts relevant to education insecurity in English, French, and Arabic for countries in Africa and the Middle East. The visualisation combines the Twitter results with reports on education insecurity from the Armed Conflict Location & Event Data (ACLED) project, to test for correlations.
Updated
26 January 2021
| Dataset date: February 01, 2020-August 31, 2020
This dataset updates: Every six months
This dataset represents the geographical distribution of Twitter users and tweets related to Coronavirus (COVID-19) pandemic at three levels. The data was collected and processed by the AIDR system (http://aidr.qcri.org). See the individual resources/files for more details about the datasets.
Updated
18 November 2018
| Dataset date: September 16, 2018-September 26, 2018
This dataset updates: Never
This is a Twitter dataset collected during the typhoon Mangkhut 2018 in the Philippines. The data was collected, processed, and analyzed by the AIDR (http://aidr.qcri.org) platform using state of the art machine learning techniques. The data includes the reports of number of injured and dead people, infrastructure damage reports, missing or found people, urgent needs and donation offers for each hour. Due to Twitter TOS, we do not share full tweets content on HDX. Please contact us via HDX or on aidr.qcri@gmail.com to get tweet ids of the dataset along with a tool which can be used to rehydrate tweets from tweet ids.
Updated
10 July 2018
| Dataset date: August 25, 2017-September 05, 2017
This dataset updates: Never
This resource is comprised of Twitter data collected and processed by the AIDR system during the 2017 hurricane Harvey. The data contains information about number of people affected, injured, dead, reports of damages, missing people and so on. The data was automatically classified using state of the art machine learning techniques.
