EAGER: Supporting GUI-Based Text Analytics on Social Media Data by Non-Technical Users

EAGER:支持非技术用户对社交媒体数据进行基于 GUI 的文本分析

基本信息

  • 批准号:
    1745673
  • 负责人:
  • 金额:
    $ 20万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2017
  • 资助国家:
    美国
  • 起止时间:
    2017-08-01 至 2019-07-31
  • 项目状态:
    已结题

项目摘要

A wealth of information is being created at an increasingly fast rate from social media sources such as Twitter. Many researchers need text analytics on social media data to obtain domain-specific insights, by doing various computational tasks such as keyword search, regular expression, natural language processing, and sentiment analysis. A main challenge is their lack of IT background, making it hard for them to conduct research efficiently. In addition, very often they need to use machine learning models to do deep analysis, and the data-preparation process for generating labeled instances for training models can be time consuming and labor intensive. This project studies how to support text analytics on social media data by users who do not have a strong IT background. It develops an open-source system with the following goals: (1) modularizing common text computation as basic operators; (2) providing a graphic user interface (GUI) for users to form a workflow plan declaratively without writing code; (3) supporting text analytics as a Web-based service; and (4) supporting indexing whenever possible to improve performance. The system has been under development on Github for more than 15 months with more than 30 committers and 21 thousand lines of high-quality source code. An initial prototype is setup and used by Public Health researchers at UC Irvine to analyze Twitter data. The techniques are general-purpose, systems-oriented, and can benefit many other domains as well.
大量信息正以越来越快的速度从Twitter等社交媒体来源中产生。许多研究人员需要对社交媒体数据进行文本分析,通过执行各种计算任务(如关键字搜索、正则表达式、自然语言处理和情感分析)来获得特定领域的见解。一个主要的挑战是他们缺乏IT背景,这使得他们很难有效地进行研究。此外,他们经常需要使用机器学习模型来进行深度分析,并且为训练模型生成标记实例的数据准备过程可能非常耗时且劳动密集。该项目研究如何支持没有强大IT背景的用户对社交媒体数据进行文本分析。它开发了一个开源系统,具有以下目标:(1)将通用文本计算模块化为基本运算符;(2)为用户提供图形用户界面(GUI),以声明方式形成工作流计划,而无需编写代码;(3)支持文本分析作为基于Web的服务;(4)尽可能支持索引以提高性能。该系统已经在Github上开发了15个多月,有30多个提交者和2.1万行高质量的源代码。加州大学欧文分校的公共卫生研究人员建立并使用了一个初始原型来分析Twitter数据。这些技术是通用的,面向系统的,也可以使许多其他领域受益。

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)
Use of Twitter data to improve Zika virus surveillance in the United States during the 2016 epidemic
  • DOI:
    10.1186/s12889-019-7103-8
  • 发表时间:
    2019-06-14
  • 期刊:
  • 影响因子:
    4.5
  • 作者:
    Masri, Shahir;Jia, Jianfeng;Wu, Jun
  • 通讯作者:
    Wu, Jun
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Chen Li其他文献

Robot needle-punching for manufacturing composite preforms
用于制造复合材料预成型件的机器人针刺
A novel grey seasonal model based on cycle accumulation generation for forecasting energy consumption in China
基于循环累积生成的新型中国能源消费灰色季节模型
  • DOI:
    10.1016/j.cie.2021.107725
  • 发表时间:
    2021-10
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Zhou Weijie;Pan Jiao;Tao Huihui;Ding Song;Chen Li;Zhao Xiaoke
  • 通讯作者:
    Zhao Xiaoke
Insight-HXMT Observations of Swift J0243.6 6124 during Its 2017-2018 Outburst
Insight-HXMT 对 Swift J0243.6 6124 2017-2018 年爆发期间的观测
  • DOI:
    10.3847/1538-4357/ab22b1
  • 发表时间:
    2019
  • 期刊:
  • 影响因子:
    4.9
  • 作者:
    Zhang Yue;Ge MinYu;Song LiMing;Zhang ShuangNan;Qu JinLu;Zhang Shu;Doroshenko Victor;Tao Lian;Ji Long;Gungor Can;Santangelo Andrea;Shi ChangSheng;Chang Zhi;Chen Gang;Chen Li;Chen TianXiang;Chen Yong;Chen YiBao;Cui Wei;Cui WeiWei;Deng JingKang;Dong YongWei
  • 通讯作者:
    Dong YongWei
Retrospective clinical analysis of risk factors associated with failed short implants.
与短种植体失败相关的危险因素的回顾性临床分析。
  • DOI:
    10.1111/clr.233_13509
  • 发表时间:
    2019-09
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Chen Li;Yang Tao;Yang Guangwen;Zhou Na;Dong Heng;Mou Yongbin
  • 通讯作者:
    Mou Yongbin

Chen Li的其他文献

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{{ truncateString('Chen Li', 18)}}的其他基金

Travel: Request for Student Travel Support for ICDE 2023
旅行:申请 ICDE 2023 学生旅行支持
  • 批准号:
    2300205
  • 财政年份:
    2023
  • 资助金额:
    $ 20万
  • 项目类别:
    Standard Grant
How Orb-Weaver Spiders Use Leg posture to Modulate Vibration Sensing of Prey on Webs
圆织蜘蛛如何利用腿部姿势来调节网上猎物的振动感知
  • 批准号:
    2310707
  • 财政年份:
    2023
  • 资助金额:
    $ 20万
  • 项目类别:
    Continuing Grant
Collaborative Research: Frameworks: Simulating Autonomous Agents and the Human-Autonomous Agent Interaction
协作研究:框架:模拟自主代理和人机交互
  • 批准号:
    2209795
  • 财政年份:
    2022
  • 资助金额:
    $ 20万
  • 项目类别:
    Standard Grant
ISS: Transient Behavior of Flow Condensation and Its Impacts on Condensation Rate
ISS:流动冷凝的瞬态行为及其对冷凝率的影响
  • 批准号:
    2224438
  • 财政年份:
    2022
  • 资助金额:
    $ 20万
  • 项目类别:
    Standard Grant
Scattering Selection Rules of Chiral Phonons and Thermal Transport
手性声子的散射选择规则与热传输
  • 批准号:
    2227947
  • 财政年份:
    2022
  • 资助金额:
    $ 20万
  • 项目类别:
    Standard Grant
ISS: Understanding the Gravity Effect on Flow Boiling Through High-Resolution Experiments and Machine Learning
ISS:通过高分辨率实验和机器学习了解重力对流动沸腾的影响
  • 批准号:
    2126437
  • 财政年份:
    2021
  • 资助金额:
    $ 20万
  • 项目类别:
    Standard Grant
III: Medium: Collaborative Research: Collaborative Machine-Learning-Centric Data Analytics at Scale
III:媒介:协作研究:以机器学习为中心的大规模协作数据分析
  • 批准号:
    2107150
  • 财政年份:
    2021
  • 资助金额:
    $ 20万
  • 项目类别:
    Continuing Grant
CAREER: Anisotropic Suppression of Lattice Thermal Conductivity through the Interaction between Phonons and Thermal Magnetic Excitations
职业:通过声子和热磁激发之间的相互作用对晶格热导率进行各向异性抑制
  • 批准号:
    1750786
  • 财政年份:
    2018
  • 资助金额:
    $ 20万
  • 项目类别:
    Standard Grant
EPRI: On-demand Sweating-Boosted Air Cooled Heat-Pipe Condensers for Green Power Plants
EPRI:用于绿色发电厂的按需发汗增压风冷热管冷凝器
  • 批准号:
    1357920
  • 财政年份:
    2014
  • 资助金额:
    $ 20万
  • 项目类别:
    Continuing Grant
Nanotip-Induced Boundary Layers to Enhance Flow Boiling in Microchannels
纳米尖端诱导边界层增强微通道中的流动沸腾
  • 批准号:
    1336443
  • 财政年份:
    2013
  • 资助金额:
    $ 20万
  • 项目类别:
    Standard Grant

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