We invite contributions from researchers in computer science, NLP, ML, AI, socio-political sciences, conflict analysis and forecasting, peace studies, as well as computational social science scholars involved in the collection and utilization of socio-political event data. Social and political scientists will be interested in reporting and discussing their approaches and observe what the state-of-the-art text processing systems can achieve for their domain. Computational scholars will have the opportunity to illustrate the capacity of their approaches in this domain and benefit from being challenged by real-world use cases. Academic workshops specific to tackling event information in general or for analyzing text in specific domains such as health, law, finance, and biomedical sciences have significantly accelerated progress in these topics and fields, respectively. However, there is not a comparable effort for handling socio-political events. We hope to fill this gap and contribute to social and political sciences in a similar spirit. We invite work on all aspects of automated coding of socio-political events from mono- or multi-lingual text sources. This includes (but is not limited to) the following topics
Extracting events in and beyond a sentence
Training data collection and annotation processes
Event coreference detection
Event-event relations, e.g., subevents, main events, causal relations
Event dataset evaluation in light of reliability and validity metrics
Defining, populating, and facilitating event schemas and ontologies
Automated tools and pipelines for event collection related tasks
Lexical, Syntactic, and pragmatic aspects of event information manifestation
Development and analysis of rule-based, ML, hybrid, and human-in-the-loop approaches for creating event datasets
COVID-19 related socio-political events
Applications of event databases
Online social movements
Bias and fairness of the sources and event datasets
Estimating what is missing in event datasets using internal and external information
Novel event detection
Release of new event datasets
Ethics, misinformation, privacy, and fairness concerns pertaining to event datasets
Copyright issues on event dataset creation, dissemination, and sharing
Qualities of the event information on various online and offline platforms