C
Chris Emmery
Researcher at Tilburg University
Publications - 20
Citations - 363
Chris Emmery is an academic researcher from Tilburg University. The author has contributed to research in topics: Computer science & Stylometry. The author has an hindex of 6, co-authored 16 publications receiving 232 citations. Previous affiliations of Chris Emmery include University of Antwerp.
Papers
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Journal ArticleDOI
Automatic detection of cyberbullying in social media text
Cynthia Van Hee,Gilles Jacobs,Chris Emmery,Bart Desmet,Els Lefever,Ben Verhoeven,Guy De Pauw,Walter Daelemans,Veronique Hoste +8 more
TL;DR: This paper describes the collection and fine-grained annotation of a cyberbullying corpus for English and Dutch and performs a series of binary classification experiments to determine the feasibility of automatic cyberbullies detection.
Journal ArticleDOI
Current Limitations in Cyberbullying Detection: on Evaluation Criteria, Reproducibility, and Data Scarcity
Chris Emmery,Chris Emmery,Ben Verhoeven,Guy De Pauw,Gilles Jacobs,Cynthia Van Hee,Els Lefever,Bart Desmet,Veronique Hoste,Walter Daelemans +9 more
TL;DR: An effective crowdsourcing method is presented: simulating real-life bullying scenarios in a lab setting generates plausible data that can be effectively used to enrich real data, and largely circumvents the restrictions on data that could be collected, and increases classifier performance.
Proceedings Article
Evaluating Unsupervised Dutch Word Embeddings as a Linguistic Resource
TL;DR: The authors demonstrate the performance of multiple types of embeddings, created with both count and prediction-based architectures on a variety of corpora, in two language-specific tasks: relation evaluation, and dialect identification.
Posted Content
Evaluating Unsupervised Dutch Word Embeddings as a Linguistic Resource
TL;DR: This paper demonstrates the performance of multiple types of embeddings, created with both count and prediction-based architectures on a variety of corpora, in two language-specific tasks: relation evaluation, and dialect identification.
Proceedings ArticleDOI
Simple Queries as Distant Labels for Predicting Gender on Twitter
TL;DR: This paper demonstrates the effectiveness of gathering distant labels for self-reported gender on Twitter using simple queries and offers a cheap, extensible, and fast alternative that can be employed beyond the task of gender classification.