event extraction

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URL: https://emw.ku.edu.tr/case-2023/

Paper submission deadline: 10 July 2023
Paper acceptance notification: 5 August 2023
Paper camera-ready: 25 August 2023
Workshop dates: 7-8 September 2023
Dates and deadlines for the shared task are below.

Softconf page of the workshop: https://softconf.com/ranlp23/CASE/

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 has not been a comparable effort for handling Socio-political Events (SPEs). We fill this gap. We invite work on all aspects of automated coding and analysis of SPEs and events in general from mono- or multi-lingual text sources. This includes (but is not limited to) the following topics

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URL: https://emw.ku.edu.tr/case-2022/

Event information detection consists of multiple subsequent steps that could drastically affect the quality of the resulted event database. Thus, we believe one must consider a complete scenario that consists of document and sentence classification as relevant or not, event coreference resolution, event information extraction, and event classification in relation to an event taxonomy, and test the results on a list of events created manually to determine performance of the state-of-the-art on this task.

Today, the unprecedented quantity of easily accessible data on social, political, and economic processes offers ground-breaking potential in guiding data-driven analysis in social and human sciences and in driving informed policy-making processes. The need for precise and high-quality information about a wide variety of events ranging from political violence, environmental catastrophes, and conflict, to international economic and health crises has rapidly escalated (Porta and Diani, 2015; Coleman et al. 2014).

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.

Today, the unprecedented quantity of easily accessible data on social, political, and economic processes offers ground-breaking potential in guiding data-driven analysis in social and human sciences and in driving informed policy-making processes. The need for precise and high-quality information about a wide variety of events ranging from political violence, environmental catastrophes, and conflict, to international economic and health crises has rapidly escalated (Porta and Diani, 2015; Coleman et al. 2014).

Automatic Extraction of Socio-Political Events from News (AESPEN) is a workshop, which promotes the advances and synergies in the field of detection of socio-political events, creation of new event datasets, developments of new approaches and systems, based on state-of-the art machine learning (ML) and Natural Language Processing (NLP) technologies in the scope of Language Resources and Evaluation Conference (LREC 2020).

The 1st Joint Workshop on Narrative Understanding, Storylines, and Events (NUSE) @ ACL 2020
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Paper submissions due: April 6, 2020
Notification of acceptance: May 4, 2020
Camera-ready papers due: May 18, 2020
Workshop: July 9, 2020

Collecting protest and conflict event information from news sources enables historical and comparative studies of social movements in social and political sciences. As the collection of event data covers more countries, longer time periods, and more details and granularity, which are more abound in local sources in comparison to international resources, their utility in social science applications multiplies.