Pular para o conteúdo principal

ETHNOS_APP

Início • Busca • Periódicos • Lista 0

Finding Dutch natives in online forums

Dados Bibliográficos

ID13119752
AutoresBernard van den Boom (Leiden University), Cor J Veenman (0000-0002-2645-1198, Leiden University, autor correspondente)
Ano2018
Volume3
Fascículo3
Páginas230-239
Data de publicação2018-07-03
Open AccessSim
TipoARTICLE
PeriódicoForensic Sciences Research (JOURNAL)
Identificadores do periódicoISSN: 2471-1411 • E-ISSN: 2096-1790
EditoraTaylor & Francis (PUBLISHER • GB)
DOI10.1080/20961790.2018.1482042
PMID30483673
OpenAlexW2893041095
IdiomaEN
Referências citadas22

Law enforcement agencies have a restricted area in which their powers apply, which is called their jurisdiction. These restrictions also apply to the Internet. However, on the Internet, the physical borders of the jurisdiction, typically country borders, are hard to discover. In our case, it is hard to establish whether someone involved in criminal online behavior is indeed a Dutch citizen. We propose a way to overcome the arduous task of manually investigating whether a user on an Internet forum is Dutch or not. More precisely, we aim to detect that a given English text is written by a Dutch native author. To develop a detector, we follow a machine learning approach. Therefore, we need to prepare a specific training corpus. To obtain a corpus that is representative for online forums, we collected a large amount of English forum posts from Dutch and non-Dutch authors on Reddit. To learn a detection model, we used a bag-of-words representation to capture potential misspellings, grammatical errors or unusual turns of phrases that are characteristic of the mother tongue of the authors. For this learning task, we compare the linear support vector machine and regularized logistic regression using the appropriate performance metrics f 1 score, precision, and average precision. Our results show logistic regression with frequency-based feature selection performs best at predicting Dutch natives. Further study should be directed to the general applicability of the results that is to find out if the developed models are applicable to other forums with comparable high performance

Internet privacy · Jurisdiction · Law enforcement · Logistic regression · Machine learning · Natural language processing · Political science · Representation (politics · Selection (genetic algorithm · Support vector machine · Task (project management · The Internet · World Wide Web · Authorship Attribution and Profiling · Computer Science · Law · Natural Language Processing Techniques · Spam and Phishing Detection · Artificial Intelligence

  • The Regression Analysis of Binary Sequences

    Open Access•D R Cox•Journal of the Royal Statistical…•1958

  • The use of the area under the ROC curve in the evaluation of machine learning algorithms

    Open Access•Andrew P Bradley•Pattern Recognition•1997

  • Machine learning in automated text categorization

    Open Access•Fabrizio Sebastiani•ACM Computing Surveys•2002

  • Regression Shrinkage and Selection Via the Lasso

    Open Access•Robert Tibshirani•Journal of the Royal Statistical…•1996

Altamente citadoNão
Abrir DOISci-HubOpen Access
Ethnos_APP • Projeto Open Source • Licença MIT • Frontend v2.0.0 • Privacidade e Cookies • Documentação da API: api.ethnos.app/docs • Código da API: GitHub • DOI: 10.5281/zenodo.17049435 • Código do Frontend: GitHub • DOI: 10.5281/zenodo.17050053 • cruz.rio.br • Expectantes Misericordiae