Data Science Meets Law

Hod, Shlomi; Chagal-Feferkorn, Karni; Elkin-Koren, Niva; Gal, Avigdor

doi:10.2139/ssrn.4077216

Cited by 1 publication

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“…Scholars are exploring the integration of data science with the law itself, and courts are experimenting with the integration of data science into judicial trials, such as China's smart courts (Zheng, 2020), which expect to use data science techniques to free lawyers and judges from the drudgery of their work. Universities and academic institutions are also experimenting with the integration of data science and law to train people who can adapt to future directions (Hod et al, 2022). Some data science applications closely related to law practice have been developed in recent years.…”

Section: The Internal Impact Of Data Science On Legal Practicementioning

confidence: 99%

Data Science Applications and Implications in Legal Studies: A Perspective Through Topic Modelling

Tan¹,

Wan²,

Yan³

et al. 2022

Journal of Data Science

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Law and legal studies has been an exciting new field for data science applications whereas the technological advancement also has profound implications for legal practice. For example, the legal industry has accumulated a rich body of high quality texts, images and other digitised formats, which are ready to be further processed and analysed by data scientists. On the other hand, the increasing popularity of data science has been a genuine challenge to legal practitioners, regulators and even general public and has motivated a long-lasting debate in the academia focusing on issues such as privacy protection and algorithmic discrimination. This paper collects 1236 journal articles involving both law and data science from the platform Web of Science to understand the patterns and trends of this interdisciplinary research field in terms of English journal publications. We find a clear trend of increasing publication volume over time and a strong presence of high-impact law and political science journals. We then use the Latent Dirichlet Allocation (LDA) as a topic modelling method to classify the abstracts into four topics based on the coherence measure. The four topics identified confirm that both challenges and opportunities have been investigated in this interdisciplinary field and help offer directions for future research.

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Section: The Internal Impact Of Data Science On Legal Practicementioning

confidence: 99%