Automatically identifying eviction cases and outcomes within case law of Dutch Courts of First Instance

Masha Medvedeva; Thijmen Dam; Martijn Wieling; Michel Vols

doi:10.3233/FAIA210312

Automatically identifying eviction cases and outcomes within case law of Dutch Courts of First Instance

Masha Medvedeva^*, Thijmen Dam, Martijn Wieling, Michel Vols

^*Corresponding author voor dit werk

Onderzoeksoutput › Academic › peer review

4 Citaten (Scopus)

91 Downloads (Pure)

Samenvatting

In this paper we attempt to identify eviction judgements within all case law published by Dutch courts in order to automate data collection, previously conducted manually. To do so we performed two experiments. The first focused on identifying judgements related to eviction, while the second focused on identifying the outcome of the cases in the judgements (eviction vs. dismissal of the landlord’s claim). In the process of conducting the experiments for this study, we have created a manually annotated dataset with eviction-related judgements and their outcomes.

Originele taal-2	English
Titel	Legal Knowledge and Information Systems
Redacteuren	Erich Schweighofer
Uitgeverij	IOS Press
Pagina's	13-22
Aantal pagina's	10
ISBN van elektronische versie	978-1-64368-253-2
ISBN van geprinte versie	978-1-64368-252-5
DOI's	https://doi.org/10.3233/FAIA210312
Status	Published - 2021
Evenement	JURIX 2021: The Thirty-fourth Annual Conference - Vilnius, Lithuania Duur: 8-dec.-2021 → 10-dec.-2021

Publicatie series

Naam	Frontiers in Artificial Intelligence and Applications
Uitgeverij	IOS Press
Volume	346
ISSN van geprinte versie	0922-6389
ISSN van elektronische versie	1879-8314

Conference

Conference	JURIX 2021: The Thirty-fourth Annual Conference
Land/Regio	Lithuania
Stad	Vilnius
Periode	08/12/2021 → 10/12/2021

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10.3233/FAIA210312Licentie: CC BY-NC

FAIA-346-FAIA210312Final publisher's version, 234 KBLicentie: CC BY-NC

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Permanente koppeling

EVICT : The Impact of the International Right to Housing on National Legal Discourse: Using Data Science Techniques to Analyse Eviction Litigation
Vols, M. (Hoofdonderzoeker), Wieling, M. (Researcher), Bruijn, M. (Postdoc), Hoops, B. (CoPI), Roorda, B. (Member), Mohammadi, M. (Postdoc), Quintiá Pastrana, A. (Postdoc), Whitehouse, L. (Advisor), Schmid, C. (Advisor), van Dijck, G. (Advisor), Arts, K. (Advisor), Prakken, H. (Advisor), de Vries, J. (Advisor) & Zauner-Lohmeyer, K. (Advisor)
01/01/2021 → …
Project: Research

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Citeer dit

@inproceedings{e9bf5727d0fa4c0281b8dc16a95c1bd0,

title = "Automatically identifying eviction cases and outcomes within case law of Dutch Courts of First Instance",

abstract = "In this paper we attempt to identify eviction judgements within all case law published by Dutch courts in order to automate data collection, previously conducted manually. To do so we performed two experiments. The first focused on identifying judgements related to eviction, while the second focused on identifying the outcome of the cases in the judgements (eviction vs. dismissal of the landlord{\textquoteright}s claim). In the process of conducting the experiments for this study, we have created a manually annotated dataset with eviction-related judgements and their outcomes.",

author = "Masha Medvedeva and Thijmen Dam and Martijn Wieling and Michel Vols",

year = "2021",

doi = "10.3233/FAIA210312",

language = "English",

isbn = "978-1-64368-252-5",

series = "Frontiers in Artificial Intelligence and Applications",

publisher = "IOS Press",

pages = "13--22",

editor = "Erich Schweighofer",

booktitle = "Legal Knowledge and Information Systems",

note = "JURIX 2021: The Thirty-fourth Annual Conference ; Conference date: 08-12-2021 Through 10-12-2021",

}

Medvedeva, M, Dam, T, Wieling, M & Vols, M 2021, Automatically identifying eviction cases and outcomes within case law of Dutch Courts of First Instance. in E Schweighofer (uitgave), Legal Knowledge and Information Systems. Frontiers in Artificial Intelligence and Applications, vol. 346, IOS Press, blz. 13-22, JURIX 2021: The Thirty-fourth Annual Conference, Vilnius, Lithuania, 08/12/2021. https://doi.org/10.3233/FAIA210312

Automatically identifying eviction cases and outcomes within case law of Dutch Courts of First Instance. / Medvedeva, Masha; Dam, Thijmen; Wieling, Martijn et al.
Legal Knowledge and Information Systems. uitgave / Erich Schweighofer. IOS Press, 2021. blz. 13-22 (Frontiers in Artificial Intelligence and Applications; Vol. 346).

Onderzoeksoutput › Academic › peer review

TY - GEN

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AU - Medvedeva, Masha

AU - Dam, Thijmen

AU - Wieling, Martijn

AU - Vols, Michel

PY - 2021

Y1 - 2021

N2 - In this paper we attempt to identify eviction judgements within all case law published by Dutch courts in order to automate data collection, previously conducted manually. To do so we performed two experiments. The first focused on identifying judgements related to eviction, while the second focused on identifying the outcome of the cases in the judgements (eviction vs. dismissal of the landlord’s claim). In the process of conducting the experiments for this study, we have created a manually annotated dataset with eviction-related judgements and their outcomes.

AB - In this paper we attempt to identify eviction judgements within all case law published by Dutch courts in order to automate data collection, previously conducted manually. To do so we performed two experiments. The first focused on identifying judgements related to eviction, while the second focused on identifying the outcome of the cases in the judgements (eviction vs. dismissal of the landlord’s claim). In the process of conducting the experiments for this study, we have created a manually annotated dataset with eviction-related judgements and their outcomes.

U2 - 10.3233/FAIA210312

DO - 10.3233/FAIA210312

M3 - Conference contribution

SN - 978-1-64368-252-5

T3 - Frontiers in Artificial Intelligence and Applications

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EP - 22

BT - Legal Knowledge and Information Systems

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PB - IOS Press

T2 - JURIX 2021: The Thirty-fourth Annual Conference

Y2 - 8 December 2021 through 10 December 2021

ER -

Automatically identifying eviction cases and outcomes within case law of Dutch Courts of First Instance

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Projecten

EVICT : The Impact of the International Right to Housing on National Legal Discourse: Using Data Science Techniques to Analyse Eviction Litigation

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