Using Citation Analysis Techniques for Computer-Assisted Legal Research in Continental Jurisdictions

Geist, Al

doi:10.2139/ssrn.1397674

Cited by 18 publications

(7 citation statements)

References 107 publications

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“…Fowler [37], Neale [84], Koniaris et al [62], Geist [38] and van Opijnen [120] present large studies of citation networks in case law. With regard to case law retrieval, citation indexes have existed for some time [132].…”

Section: Daniel Locke and Guido Zucconmentioning

confidence: 99%

“…(i) the creation of visual tools for mapping citation networks; (ii) suggestions that citations are a useful ranking feature [126]; and (iii) findings that legal citation networks exhibit similarities as compared to other networks [38] that have been used to rank results of search systems, citation networks have only been applied to ranking documents for case law retrieval in two instances.…”

Section: Daniel Locke and Guido Zucconmentioning

confidence: 99%

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Case law retrieval: problems, methods, challenges and evaluations in the last 20 years

Locke¹,

Zuccon²

2022

Preprint

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Case law retrieval is the retrieval of judicial decisions relevant to a legal question. Case law retrieval comprises a significant amount of a lawyer's time, and is important to ensure accurate advice and reduce workload. We survey methods for case law retrieval from the past 20 years and outline the problems and challenges facing evaluation of case law retrieval systems going forward. Limited published work has focused on improving ranking in ad-hoc case law retrieval. But there has been significant work in other areas of case law retrieval, and legal information retrieval generally. This is likely due to legal search providers being unwilling to give up the secrets of their success to competitors. Most evaluations of case law retrieval have been undertaken on small collections and focus on related tasks such as question-answer systems or recommender systems. Work has not focused on Cranfield style evaluations and baselines of methods for case law retrieval on publicly available test collections are not present. This presents a major challenge going forward. But there are reasons to question the extent of this problem, at least in a commercial setting. Without test collections to baseline approaches it cannot be known whether methods are promising. Works by commercial legal search providers show the effectiveness of natural language systems as well as query expansion for case law retrieval. Machine learning is being applied to more and more legal search tasks, and undoubtedly this represents the future of case law retrieval.

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Section: Daniel Locke and Guido Zucconmentioning

confidence: 99%

Section: Daniel Locke and Guido Zucconmentioning

confidence: 99%

Case law retrieval: problems, methods, challenges and evaluations in the last 20 years

Locke¹,

Zuccon²

2022

Preprint

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“…Many researchers focus on building an easy-to-use legal search engine (Barmakian, 2000;Turtle, 1995). They also explore utilizing more information, including citations (Monroy et al, 2013;Geist, 2009;Raghav et al, 2016) and legal concepts (Maxwell and Schafer, 2008;Van Opijnen and Santos, 2017). Towards the goal of calculating similarity in semantic level, deep learning methods have also been applied to LegalIR.…”

Section: Related Workmentioning

confidence: 99%

How Does NLP Benefit Legal System: A Summary of Legal Artificial Intelligence

Zhong¹,

Xiao²,

Tu³

et al. 2020

Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics

178

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Legal Artificial Intelligence (LegalAI) focuses on applying the technology of artificial intelligence, especially natural language processing, to benefit tasks in the legal domain. In recent years, LegalAI has drawn increasing attention rapidly from both AI researchers and legal professionals, as LegalAI is beneficial to the legal system for liberating legal professionals from a maze of paperwork. Legal professionals often think about how to solve tasks from rulebased and symbol-based methods, while NLP researchers concentrate more on data-driven and embedding methods. In this paper, we describe the history, the current state, and the future directions of research in LegalAI. We illustrate the tasks from the perspectives of legal professionals and NLP researchers and show several representative applications in LegalAI. We conduct experiments and provide an indepth analysis of the advantages and disadvantages of existing works to explore possible future directions. You can find the implementation of our work from https://github. com/thunlp/CLAIM.

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“…Having been rediscovered in the 1980s, citations analysis in law has progressed rapidly: notably, Fred R. Shapiro, a librarian and lecturer at Yale Law School, published numerous original studies and developed the field (Shapiro 1985(Shapiro , 1996(Shapiro , 2001bShapiro and Pearse 2012), hence being called "the founding father of a new and peculiar discipline: 'legal citology'" (Balkin and Levinson 1996, 843). Meanwhile, citations analysis has gained footholds in legal research overseas, for example, in Austria (Geist 2009), Germany (Hamann 2014c), the Netherlands (Winkels et al 2014), and for European case law at the ECJ (Panagis and Sadl 2015).…”

Section: Citations Analysismentioning

confidence: 99%

Computer-Assisted Legal Linguistics: Corpus Analysis as a New Tool for Legal Studies

Vogel¹,

Hamann²,

Gauer³

2018

Law soc. inq.

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Law exists solely in and through language. Nonetheless, systematical empirical analysis of legal language has been rare. Yet, the tides are turning: After judges at various courts (including the US Supreme Court) have championed a method of analysis called corpus linguistics, the Michigan Supreme Court held in June 2016 that this method “is consistent with how courts have understood statutory interpretation.” The court illustrated how corpus analysis can benefit legal casework, thus sanctifying twenty years of previous research into the matter. The present article synthesizes this research and introduces computer-assisted legal linguistics (CAL2) as a novel approach to legal studies. Computer-supported analysis of carefully preprocessed collections of legal texts lets lawyers analyze legal semantics, language, and sociosemiotics in different working contexts (judiciary, legislature, legal academia). The article introduces the interdisciplinary CAL2 research group (www.cal2.eu), its Corpus of German Law, and other related projects that make law more transparent.

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Using Citation Analysis Techniques for Computer-Assisted Legal Research in Continental Jurisdictions

Cited by 18 publications

References 107 publications

Case law retrieval: problems, methods, challenges and evaluations in the last 20 years

Case law retrieval: problems, methods, challenges and evaluations in the last 20 years

How Does NLP Benefit Legal System: A Summary of Legal Artificial Intelligence

Computer-Assisted Legal Linguistics: Corpus Analysis as a New Tool for Legal Studies

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