I-Corps: Artificial Intelligence driven environmental, social, and governance
I-Corps:人工智能驱动的环境、社会和治理
基本信息
- 批准号:2321155
- 负责人:
- 金额:$ 5万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2023
- 资助国家:美国
- 起止时间:2023-04-01 至 2024-09-30
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
The broader impact/commercial potential of this I-Corps project is the development of a technology that can help increase transparency and accountability in corporations' environmental, social, and governance practices. This, in turn, can encourage corporations to adopt more sustainable and responsible business practices, leading to a more sustainable future for both the environment and society. Moreover, by providing portfolio managers with comprehensive and accurate environmental, social, and governance metrics, the technology can help drive investment toward companies committed to sustainable and responsible practices. This shift in investment patterns can further encourage corporations to prioritize environmental, social, and governance considerations, leading to a virtuous cycle of increased environmental, social, and governance accountability and sustainability. The technology primarily aims to aid portfolio managers in assessing corporations' environmental, social, and governance responsibilities. In addition to investment advisers, the technology can help corporations improve their environmental, social, and governance reporting. Moreover, financial consultants can benefit from the technology as they advise and lead their clients towards better environmental, social, and governance-reporting practices increasingly demanded by regulators. The technology can increase environmental and social responsibilities within vulnerable communities and improve global governance.This I-Corps project is based on the development of technology to address issues with existing environmental, social, and governance standards and includes the environmental, social, and governance Knowledge Meta Model that consists of environmental, social, and governance Taxonomy and Ontology. The model analyzes environmental, social, and governance-related documents, including Securities and Exchange Commission Reports, environmental, social, and governance news, and social media posts from Twitter and Reddit, and creates a labeled environmental, social, and governance-related dataset. It further employs an environmental, social, and governance name, a Relation extraction model, multilabel classification for the taxonomy elements, and sentiment detection for environmental, social, and governance texts. These models are used to create the environmental, social, and governance Knowledge Graph Construction pipeline, which transforms environmental, social, and governance-related text into knowledge graphs. The constructed pipeline is used in real-time to convert texts from company reports and media documents into knowledge graphs. The methodology identifies discrepancies between the two sources using a graph comparison algorithm and reports any differences and inconsistencies between what the company reports and what the media writes.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.
这个I-Corps项目更广泛的影响/商业潜力是开发一种技术,可以帮助提高公司环境,社会和治理实践的透明度和问责制。这反过来又可以鼓励企业采取更可持续和负责任的商业做法,为环境和社会带来更可持续的未来。此外,通过为投资组合经理提供全面准确的环境、社会和治理指标,该技术可以帮助推动对致力于可持续和负责任实践的公司的投资。这种投资模式的转变可以进一步鼓励企业优先考虑环境、社会和治理因素,从而实现环境、社会和治理问责和可持续性的良性循环。该技术主要旨在帮助投资组合经理评估公司的环境,社会和治理责任。除了投资顾问,该技术还可以帮助企业改善其环境、社会和治理报告。此外,财务顾问可以从这项技术中受益,因为他们建议并引导客户实现监管机构日益要求的更好的环境,社会和治理报告实践。I-Corps项目以解决现有环境、社会和治理标准问题的技术开发为基础,包括环境、社会和治理知识Meta模型,该模型由环境、社会和治理分类学和本体论组成。该模型分析了与环境、社会和治理相关的文档,包括证券交易委员会报告、环境、社会和治理新闻以及Twitter和Reddit的社交媒体帖子,并创建了一个标记的环境、社会和治理相关数据集。它还采用了环境,社会和治理名称,关系提取模型,分类元素的多标签分类,以及环境,社会和治理文本的情感检测。这些模型用于创建环境、社会和治理知识图谱构建管道,将环境、社会和治理相关文本转换为知识图谱。构建的管道用于实时将公司报告和媒体文档中的文本转换为知识图。该方法使用图形比较算法识别两个来源之间的差异,并报告公司报道与媒体报道之间的任何差异和不一致之处。该奖项反映了NSF的法定使命,并通过使用基金会的知识价值和更广泛的影响审查标准进行评估,被认为值得支持。
项目成果
期刊论文数量(1)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Comparing the performance of ChatGPT and state-of-the-art climate NLP models on climate-related text classification tasks
比较 ChatGPT 和最先进的气候 NLP 模型在气候相关文本分类任务上的性能
- DOI:10.1051/e3sconf/202343602004
- 发表时间:2023
- 期刊:
- 影响因子:0
- 作者:Trajanov, Dimitar;Lazarev, Gorgi;Chitkushev, Ljubomir;Vodenska, Irena
- 通讯作者:Vodenska, Irena
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Irena Vodenska其他文献
News sentiment analysis in the US and Japan using deep learning methods
使用深度学习方法进行美国和日本的新闻情感分析
- DOI:
- 发表时间:
2019 - 期刊:
- 影响因子:0
- 作者:
Wataru Souma;Irena Vodenska;Hideaki Aoyama - 通讯作者:
Hideaki Aoyama
リモートセンシングによる液状化被害の広域把握
利用遥感技术大范围了解液化损害
- DOI:
- 发表时间:
2018 - 期刊:
- 影响因子:0
- 作者:
Wataru Souma;Irena Vodenska;Hideaki Aoyama;佐藤公俊;松岡昌志 - 通讯作者:
松岡昌志
Atomistic approach to the Nd-Fe-B magnet; Coercivity at finite temperatures
Nd-Fe-B 磁体的原子方法;
- DOI:
- 发表时间:
2020 - 期刊:
- 影响因子:0
- 作者:
Hiroshi Iyetomi;Hideaki Aoyama;Yoshi Fujiwara;Wataru Souma;Irena Vodenska;and Hiroshi Yoshikawa;Yuzuru Sato;Seiji Miyashita - 通讯作者:
Seiji Miyashita
From stress testing to systemic stress testing: The importance of macroprudential regulation
从压力测试到系统性压力测试:宏观审慎监管的重要性
- DOI:
10.1016/j.jfs.2020.100803 - 发表时间:
2021 - 期刊:
- 影响因子:5.4
- 作者:
Irena Vodenska;Hideaki Aoyama;Alexander P Becker;Yoshi Fujiwara;Hiroshi Iyetomi;Eliza Lungu - 通讯作者:
Eliza Lungu
RIAM-COMPACTの高機能化と性能評価
RIAM-COMPACT的高功能和性能评估
- DOI:
- 发表时间:
2017 - 期刊:
- 影响因子:0
- 作者:
Wataru Souma;Irena Vodenska;Hideaki Aoyama;内田孝紀 - 通讯作者:
内田孝紀
Irena Vodenska的其他文献
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{{ truncateString('Irena Vodenska', 18)}}的其他基金
EAGER: Modeling systemic risk: Finding precursors of emerging financial crises
EAGER:系统性风险建模:寻找新兴金融危机的前兆
- 批准号:
1452061 - 财政年份:2014
- 资助金额:
$ 5万 - 项目类别:
Standard Grant
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