A Concise Report of the 7th Workshop on Challenges and Applications of Automated Extraction of Socio-political Events from Text (2024)

Abstract: In this paper, we provide a brief overview of the 7th workshop on Challenges and Applications of Automated Extraction of Socio-political Events from Text (CASE) co-located with EACL 2024. This workshop consisted of regular papers, system description papers submitted by shared task participants, and overview papers of shared tasks held. This workshop series has been bringing together experts and enthusiasts from technical and social science fields, providing a platform for better understanding event information. This workshop not only advances text-based event extraction but also facilitates research in event extraction in multimodal settings.

## introduction in today's digital era, the voluminous and readily available data on socio-political, economic, and environmental phenomena hold transformative potential for data-driven analysis in the social and human sciences @xcite . this wealth of data supports informed policymaking by providing comprehensive insights into complex issues ranging from political unrest and environmental disasters to global health and economic crises @xcite . the rising demand by governments, international organizations, and ngos for high-quality, actionable information underscores the critical role of data in addressing challenges, aiding those impacted by crises, and enhancing citizen welfare in various domains @xcite . recent advancements underscore the importance of leveraging big data for social good, highlighting how data-driven approaches can revolutionize our understanding and intervention strategies in critical areas such as humanitarian aid, healthcare, and environmental protection. @xcite introduce a privacy-preserving data analysis system that offers both privacy guarantees for individuals and statistical validity for researchers, facilitating the use of sensitive data in social science research. furthermore, crowd-sourced text analysis, as discussed by @xcite , represents a paradigm shift in how data is collected and analyzed, enabling rapid, flexible, and reproducible data production that matches expert-level accuracy. the intersection of data science with policy analysis suggests a promising avenue for integrating data-driven insights into decision-making processes. @xcite highlight the convergence of data science and policy analysis, indicating an emergent cross-disciplinary domain where data science accelerates and enriches policy research. this integration is crucial for developing effective policies that are informed by empirical data and grounded in a deep understanding of complex societal dynamics. thus, it is evident that data science is instrumental in devising strategies to prevent or mitigate conflicts, deliver aid to affected populations, enhance the well-being of citizens, and safeguard them through a multitude of approaches. the public's resistance to covid-19 measures during @xcite @xcite and the conflict between russia and ukraine @xcite serve as prime instances of the critical need to harness this data for real-world impact, highlighting the public's growing demand for timely information regarding mass gatherings and societal trends. in this context, the workshop titled 'challenges and applications of automated extraction of socio-political events from text' (case 2024) plays a pivotal role. organized as part of eacl 2024, the seventh edition of this workshop marks the continuation of a workshop series that has been ongoing since its inception @xcite @xcite . this workshop aims to explore the advancements and hurdles in the automated extraction of socio-political events from textual data, offering a platform for discussing the latest research findings, innovative methodologies, and the future of automated text analysis in capturing and interpreting complex social phenomena. the workshop encompasses a range of activities, including presentations of accepted papers, shared tasks that challenge participants, and keynote speeches from leading experts in the field, providing valuable insights into the state of the art and fostering collaboration among researchers and practitioners. this paper is a brief overview giving insights into the wide range of activities at case 2024. ## accepted papers this year, seven papers were accepted out of twelve submissions. below, we provide brief descriptions of accepted papers. the results highlight the importance of selecting appropriate models trained on similar data to the task domain. though discontent classification is nuanced, the authors show it can help filter relevant messages and identify possible protests if models optimized for low false positives are used. ## shared tasks this edition of the workshop featured two shared tasks. in addition to these two tasks, the workshop also welcomed submissions to previously organized shared tasks in earlier editions of case workshops. ## conclusion in conclusion, the diverse range of papers and shared tasks presented at the workshop, from multimodal data analysis to fine-tuning language models for detecting hate speech and extracting event timelines, underscores the potential of automated text analysis in understanding complex socio-political phenomena. the workshop's emphasis on addressing real-world issues, such as understanding discourse related to climate change, online hate speech, and misinformation, through state-of-theart computational techniques, not only sets new benchmarks for future research but also highlights the growing commitment within the community to leverage natural language processing for social good. in the coming years, the workshop will continue to advance the intersection of natural language processing and social good, promoting cutting-edge research and interdisciplinary collaboration to tackle complex socio-political challenges through automated text analysis.