Search Results for author: Marijn Schraagen

Found 8 papers, 3 papers with code

Public Sentiment on Governmental COVID-19 Measures in Dutch Social Media

no code implementations EMNLP (NLP-COVID19) 2020 Shihan Wang, Marijn Schraagen, Erik Tjong Kim Sang, Mehdi Dastani

Public sentiment (the opinion, attitude or feeling that the public expresses) is a factor of interest for government, as it directly influences the implementation of policies.

Sentiment Analysis

Folktale similarity based on ontological abstraction

no code implementations GWC 2016 Marijn Schraagen

The method is applied on a corpus of Dutch folktales and evaluated using a comparison to traditional folktale similarity analysis based on the Aarne–Thompson–Uther (ATU) classification system.

Classification

Negation detection in Dutch clinical texts: an evaluation of rule-based and machine learning methods

1 code implementation1 Sep 2022 Bram van Es, Leon C. Reteig, Sander C. Tan, Marijn Schraagen, Myrthe M. Hemker, Sebastiaan R. S. Arends, Miguel A. R. Rios, Saskia Haitjema

As structured data are often insufficient, labels need to be extracted from free text in electronic health records when developing models for clinical information retrieval and decision support systems.

Information Retrieval Negation +2

Dutch General Public Reaction on Governmental COVID-19 Measures and Announcements in Twitter Data

1 code implementation12 Jun 2020 Shihan Wang, Marijn Schraagen, Erik Tjong Kim Sang, Mehdi Dastani

Given the unprecedented nature of the COVID-19 crisis, having an up-to-date representation of public sentiment on governmental measures and announcements is crucial.

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