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    Litigation Risk Detection Using Twitter Data

    Source: Journal of Legal Affairs and Dispute Resolution in Engineering and Construction:;2020:;Volume ( 012 ):;issue: 001
    Author:
    Chengyuan Diao
    ,
    Rachel Liang
    ,
    Deepak Sharma
    ,
    Qingbin Cui
    DOI: 10.1061/(ASCE)LA.1943-4170.0000356
    Publisher: ASCE
    Abstract: Construction projects are notorious for their frequent disputes and costly legal battles. This is particularly true for infrastructure projects, where technical and institutional complexity increases the risks and challenges of facing litigation. Early studies have been focused on subject matter experts’ ability to identify various risks and potential disputes. This paper presents a novel approach to estimate litigation risk using widely accessible social media data. By defining levels of legal risk and potential plaintiff’s profile, this paper presents a data-driven risk estimation model to track litigation risk in real time. The Purple Line transit project from the state of Maryland is used as an example to demonstrate the litigation risk estimation model with continuous retrieval of Twitter data for analysis. The implication and effectiveness will be discussed in this case study.
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      Litigation Risk Detection Using Twitter Data

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4265998
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    contributor authorChengyuan Diao
    contributor authorRachel Liang
    contributor authorDeepak Sharma
    contributor authorQingbin Cui
    date accessioned2022-01-30T19:47:55Z
    date available2022-01-30T19:47:55Z
    date issued2020
    identifier other%28ASCE%29LA.1943-4170.0000356.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4265998
    description abstractConstruction projects are notorious for their frequent disputes and costly legal battles. This is particularly true for infrastructure projects, where technical and institutional complexity increases the risks and challenges of facing litigation. Early studies have been focused on subject matter experts’ ability to identify various risks and potential disputes. This paper presents a novel approach to estimate litigation risk using widely accessible social media data. By defining levels of legal risk and potential plaintiff’s profile, this paper presents a data-driven risk estimation model to track litigation risk in real time. The Purple Line transit project from the state of Maryland is used as an example to demonstrate the litigation risk estimation model with continuous retrieval of Twitter data for analysis. The implication and effectiveness will be discussed in this case study.
    publisherASCE
    titleLitigation Risk Detection Using Twitter Data
    typeJournal Paper
    journal volume12
    journal issue1
    journal titleJournal of Legal Affairs and Dispute Resolution in Engineering and Construction
    identifier doi10.1061/(ASCE)LA.1943-4170.0000356
    page04519047
    treeJournal of Legal Affairs and Dispute Resolution in Engineering and Construction:;2020:;Volume ( 012 ):;issue: 001
    contenttypeFulltext
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