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Collaborative Research: HCC: Medium: Fine-grained Emotion Analysis in Crises

Collaborative Research: HCC: Medium: Fine-grained Emotion Analysis in Crises
合作研究:HCC:中:危机中的细粒度情绪分析
批准号:
2107487
负责人:
Robert Sloan
金额:
$34.76万
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

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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.
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III: Medium: Collaborative Research: Extracting and Linking AI Artifacts
  • 批准号:
    2107518
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $53.0万
  • 财政年份:
    2021
  • 负责人:
    Robert Sloan
  • 依托单位:
BIGDATA: IA: Collaborative Research: Domain Adaptation Approaches for Classifying Crisis Related Data on Social Media
  • 批准号:
    1912887
  • 项目类别:
    Standard Grant
  • 资助金额:
    $39.55万
  • 财政年份:
    2018
  • 负责人:
    Robert Sloan
  • 依托单位:
CAREER: From Data to Knowledge: Extracting and Utilizing Concept Graphs in Online Environments
  • 批准号:
    1914575
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $49.99万
  • 财政年份:
    2018
  • 负责人:
    Robert Sloan
  • 依托单位:
Designing and Evaluating a CS + Law Introduction to Computer Science
  • 批准号:
    1612455
  • 项目类别:
    Standard Grant
  • 资助金额:
    $25.44万
  • 财政年份:
    2016
  • 负责人:
    Robert Sloan
  • 依托单位:
国内基金
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Research on Quantum Field Theory without a Lagrangian Description
  • 批准号:
    24ZR1403900
  • 项目类别:
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  • 资助金额:
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  • 批准年份:
    2024
  • 负责人:
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  • 依托单位:
Cell Research
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