Updated
Live
| Dataset date: May 01, 2019-December 31, 2020
This dataset updates: Live
This dataset combines two sources of education-insecurity data:
Machine-learning-driven counts of tweets from Africa and the Middle East on the topic of education insecurity—in Arabic, English, and French—via the Artificial Intelligence for Disaster Response (AIDR) project
Human-curated reports of actual education-insecurity events in Africa and the Middle East, via the Armed Conflict Location & Event Data (ACLED) project.
Updated
January 4, 2021
| Dataset date: August 27, 2020-August 27, 2020
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).
Updated
September 24, 2020
| Dataset date: February 01, 2020-August 31, 2020
This dataset updates: Every three 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
November 18, 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
July 10, 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.
