There are 1 repository under event-data topic.
Compiled and augmented version of Crowd Counting Consortium data on U.S. protest events since 2017
Synchronise event and tracking data using dynamic programming
A couple of functions to create customized passing networks with event data by Statsbomb and tracking data by Metrica Sport
A repository for football analytics
Performance Spectrum Miner
MPEDS Annotation Interface
Event-based Background-Oriented Schlieren (T-PAMI 2023)
MOVED TO https://gitlab.com/crossref/event_data_query
This repository will contain all sorts of basic visualisation to step into the world of football analytics
MOVED TO https://gitlab.com/crossref/event_data_common
MOVED TO https://gitlab.com/crossref/event_data_user_guide
MOVED to https://gitlab.com/crossref/event_data_enquiries
an R function to ingest ACLED event data using jsonlite for ingestion and data.table for processing
MOVED https://gitlab.com/crossref/event_data_percolator
Event metadata plugin for PeerTube
Snapshots the Evidence Log into archive files
MOVED TO https://gitlab.com/crossref/event_data_heartbeat
MOVED TO https://gitlab.com/crossref/event_data_investigator
Analyzing Pace-of-Play in Soccer using Spatio-Temporal Event Data
Fork of Analytics Next (aka Analytics.js 2.0) that enables carbon copying (cc-ing) an additional endpoint
Protests are an important and well researched aspect of political behavior, making measurement validity crucial. Unlike conventional forms of behavior such as voting, protest can be difficult to observe. Most studies rely on news articles for event coding, introducing a possible selection bias. Validation is often done by comparing the characteristics of different newspaper measures or using independent sources. In this paper, I benchmark a manually and a partly automatically coded dataset from the PolDem project against a unique, large government dataset covering all extreme right demonstrations and rallies in Germany from 2005 to 2020. Coverage of events in newspapers mainly depends on the region and the number of participants. Conversely, machine learning can provide a good confidence estimate about the possible misdetection of an event. The results have important implications for the study of protests. Researchers should carefully assess the advantages and shortfalls of news media based datasets.
Some projects related to the application of Machine Learning for Sports Analytics
Offers models and utilities for event time data using point processes.
Echo Evidence Log to application logs.
MOVED TO https://gitlab.com/crossref/event_data_kafka_pusher
Sample DOIs from Crossref and DataCite and analyze their landing pages. Produce Artifacts for use in Event Data.
A simple crawler for the GDELT database