Collaborative Research: HCC: Medium: Fine-grained Emotion Analysis in Crises
Collaborative Research: HCC: Medium: Fine-grained Emotion Analysis in Crises
批准号:
2107524
负责人:
Junyi Li
金额:
$45.23万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2021
资助国家:
美国
项目状态:
未结题
起止时间:
2021-10-01 至 2025-09-30
中文摘要
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英文摘要
History is rich with situations where the same event has been interpreted completely differently by different groups of people. Through events such as the OJ Simpson case, the COVID-19 crisis, and the murder of George Floyd, we have observed disparate reactions to events that community leaders, police departments, policymakers, and everyday citizens fail to anticipate. The purpose of this project is to begin to identify social, emotional, and linguistic markers of crises (e.g., social turmoil, natural disasters, etc.) that predict the various ways people will react to the same events. This is achieved by analyzing the language of social media, a rapidly-growing source of data from which we can understand the expression and perception of emotions at a very large scale, with far-reaching potential uses from academic research to public policy.Understanding emotions, the context surrounding these emotions, and subsequent behaviors are of great value to those in a crisis, seeking information about a crisis, or helping manage responses to a crisis. This project will discover mechanisms to provide comprehensive, fine-grained emotion analysis across different social platforms, and derive robust and reliable predictive models. Fine-grained emotion analysis aims to: (1) detect expressions of emotions in a text and characterize their intensity and polarity, (2) identify the triggers causing the emotions, and (3) analyze emotion deviation (i.e., the varied emotions that people express towards the same trigger). This research will contribute annotated datasets of emotions expressed on social media across distinct crises and generalizable models equipped with deep linguistic understanding for contextualized emotion analysis. Industry and academic partners will participate by evaluating the ability of the models to work on situations and data sources different from those used to develop the models.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.
期刊论文(17)
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科研奖励(0)
会议论文
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Counterfactual Probing for the Influence of Affect and Specificity on Intergroup Bias
反事实探究情感和特异性对群体间偏见的影响
DOI:
--
发表时间:
2023
期刊:
Findings of the Association for Computational Linguistics: ACL 2023
影响因子:
--
作者:
[Govindarajan, Venkata Subrahmanyan, Beaver, David, Mahowald, Kyle, Li, Junyi Jessy]
通讯作者:
Li, Junyi Jessy
Emotion analysis and detection during COVID-19
COVID-19 期间的情绪分析和检测
DOI:
--
发表时间:
2022
期刊:
Proceedings of the Language Resources and Evaluation Conference
影响因子:
--
作者:
[Sosea, Tiberiu, Pham, Chau, Tekle, Alexander, Caragea, Cornelia, Li, Junyi Jessy]
通讯作者:
Li, Junyi Jessy
DOI:
10.18653/v1/2022.naacl-main.17
发表时间:
2022
期刊:
影响因子:
--
作者:
[Barea M. Sinno;Bernardo Oviedo;Katherine Atwell;Malihe Alikhani;J. Li]
通讯作者:
Barea M. Sinno;Bernardo Oviedo;Katherine Atwell;Malihe Alikhani;J. Li
ProtoTEx: Explaining Model Decisions with Prototype Tensors
ProtoTEX:用原型张量解释模型决策
DOI:
10.18653/v1/2022.acl-long.213
发表时间:
2022
期刊:
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics
影响因子:
--
作者:
[Das, Anubrata, Gupta, Chitrank, Kovatchev, Venelin, Lease, Matthew, Li, Junyi Jessy]
通讯作者:
Li, Junyi Jessy
DOI:
--
发表时间:
2022
期刊:
影响因子:
--
作者:
[Katherine Atwell;Remi Choi;Junyi Jessy Li;Malihe Alikhani]
通讯作者:
Katherine Atwell;Remi Choi;Junyi Jessy Li;Malihe Alikhani
共 15 条
CAREER: Discourse Processing and Content Generation for Document Simplification
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批准号:2145479
-
项目类别:Continuing Grant
-
资助金额:$54.05万
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财政年份:2022
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负责人:Junyi Li
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依托单位:
CRII:RI:A Multi-level Framework for Text Specificity
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批准号:1850153
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项目类别:Standard Grant
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资助金额:$17.45万
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财政年份:2019
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负责人:Junyi Li
-
依托单位:
国内基金
海外基金
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负责人:SATOSHI NAWATA
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依托单位:
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项目类别:专项基金项目
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资助金额:24.0万元
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负责人:程磊
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资助金额:24.0万元
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依托单位:
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