Elements: Data: Sustaining Modern Infrastructure For Political And Social Event Data

该项目通过以多种语言梳理互联网上的新闻报道，提取世界各地国家和非国家行为者之间政治和国际冲突事件的量化摘要。这会生成事件数据，即从新闻报道中提取的某人对其他人做某事的机器编码描述。该项目侧重于关于政府、个人、非政府组织、反叛团体和其他人之间的冲突与合作的政治和社会事件。该项目的主要目标是整合和扩展端到端的网络基础设施，以便国家安全、政府、学术和非政府行为者强大地创建、验证、访问和分析政治事件数据。这项提议的一个主要组成部分是继续扩大该项目与全球活动数据社区的接触。该项目扩展、产生并整合了一个动态、强大的事件数据系统，以研究全球范围内的次国家和国际冲突进程，并将其应用于国家安全和情报界的需要。该项目使用自然语言处理软件工具，通过注释政治学家、国际关系学者、社会学家和国家安全界感兴趣的政治事件来编码事件数据，分析英语和西班牙语的同期新闻报道，自动为数据分析员编码相关政治事件，并通过项目网站与其他公开事件数据一起提供数据。技术挑战包括：(1)将多语言框架进一步扩展到更多类型的活动；(2)更顺畅地更新政治行为者词典；(3)健全的数据查询和链接机制，以及面向更广泛的研究和用户社区的分析工具；(4)改进跨语文和决议的焦点位置提取方法。这将通过增加多语言比较来提高事件数据质量和事件检测。事件编码软件和界面的多语言扩展将产生检测和分析罕见和局部事件的新方法。拟议的数据库整合和查询优化将简化对现有许多开放获取事件数据集的访问，使不同社区的研究人员能够分析和比较冲突和政治进程。改进地理定位模块将允许从有偏见的训练样本中检测地点，这是一项重要的进步，因为一些政治事件，如侵犯人权行为，往往发生在新闻覆盖率较低的地点。健壮和创新的地理定位方法可以推广到其他领域的应用。扩展相关的软件和数据基础设施有助于政治学、国家安全和大数据研究界。我们还将为来自多语言新闻报道服务的各种事件数据提供强大的数据链接。可持续的网络基础设施不仅包括新闻报道的事件数据编码，还包括分析工具，其中包括R包和基于瘦客户端浏览器的数据分析界面。这项奖励反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

This project extracts quantitative summaries of political and international conflict events among national and non-state actors across the world by combing news reports across the internet in multiple languages. This generates event data, a machine-coded description of someone doing something to someone else as extracted from news reports. The project focuses on political and social events about conflict and cooperation between governments, individuals, non-governmental organizations, rebel groups, and others. The main goal of this project is to integrate and expand the end-to-end cyberinfrastructure for the robust creation, validation, access, and analysis of political event data by national security, government, academic, and non-governmental actors. A major component of this proposal is to continue to grow the project's engagement with the global event data community. This project extends, produces, and integrates a dynamic, robust system for event data to study sub-national and international conflict processes at a global scale, with applications to the needs of the national security and intelligence communities. Using natural language processing software tools to code event data by annotating the kinds of political events that are of interest to political scientists, international relations scholars, sociologists, and the national security community, the project analyzes contemporaneous news reports in English and Spanish, automatically encodes relevant political events for data analysts, and serves the data along with other open event data via the project websites. The technical challenges include: (1) additional extensions of the multilingual framework to more types of events; (2) smoother updates to political actor dictionaries; (3) robust data querying and linking mechanisms, and analytic tools for the broader research and user community; (4) improved methods for focus location extraction across languages and resolutions. This will improve event data quality and event detection through increased, multi-language comparisons. The multi-lingual extensions of the event encoding software and interface will produce novel methods for detecting and analyzing rare and local events. The proposed database integrations and query optimizations will streamline access to the many open access event datasets that exist, enabling researchers across diverse communities to analyze and compare conflict and political processes. The refinements of the geolocation modules will allow detection of locations from biased training samples, which is an important advancement since some political events, such as human rights violations, tend to occur in locations with low news coverage. The robust and innovative geolocation approaches can be carried over to other domain applications. Scaling the related software and data infrastructure aids the political science, national security and big data research communities. We also will provide robust data linkages across a diverse set of event data from multiple and multilingual news reporting services. The sustainable cyberinfrastructure not only includes the event data coding from news reports, but also analysis tools that include an R package and a thin-client browser-based analysis interface to the data. This sustains the cyberinfrastructure and creates a workforce that is able to work in both science, engineering, national security, and intelligence.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.