Výsledky vyhledávání - "Chris Emmery"

Akademický článek

Automatic detection of cyberbullying in social media text.

Autor: Cynthia Van Hee, Gilles Jacobs, Chris Emmery, Bart Desmet, Els Lefever, Ben Verhoeven, Guy De Pauw, Walter Daelemans, Véronique Hoste

Publikováno v: PLoS ONE, Vol 13, Iss 10, p e0203794 (2018)

While social media offer great communication opportunities, they also increase the vulnerability of young people to threatening situations online. Recent studies report that cyberbullying constitutes a growing problem among youngsters. Successful pre

Externí odkaz: https://doaj.org/article/9bd468aac1804ec9a9072c837072cc29

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Current limitations in cyberbullying detection: On evaluation criteria, reproducibility, and data scarcity

Autor: Ben Verhoeven, Bart Desmet, Walter Daelemans, Cynthia Van Hee, Gilles Jacobs, Guy De Pauw, Els Lefever, Veronique Hoste, Chris Emmery

Publikováno v: LANGUAGE RESOURCES AND EVALUATION
Language resources and evaluation
Language Resources and Evaluation, 55, 597-633. Springer Netherlands

The detection of online cyberbullying has seen an increase in societal importance, popularity in research, and available open data. Nevertheless, while computational power and affordability of resources continue to increase, the access restrictions o

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::39d2bd8a26fb3f264e15ae85f989af69
https://doi.org/10.1007/s10579-020-09509-1

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Cyberbullying classifiers are sensitive to model-agnostic perturbations

Autor: Chris Emmery, Akos Kádár, Grzegorz Chrupała, Daelemans, W. M. P.

Publikováno v: 13th International Conference on Language Resources and Evaluation, (LREC 2022), Juin 20-25, 2022, Marseille, France
ISSUE=13;TITLE=Language Resources and Evaluation Conference
Tilburg University-PURE

A limited amount of studies investigates the role of model-agnostic adversarial behavior in toxic content classification. As toxicity classifiers predominantly rely on lexical cues, (deliberately) creative and evolving language-use can be detrimental

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::64909f8c788adaf662fec30367ad4d6f
https://hdl.handle.net/10067/1944180151162165141

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Adversarial Stylometry in the Wild

Autor: Grzegorz Chrupała, Chris Emmery, Ákos Kádár

Publikováno v: 16th Conference of the European-Chapter-of-the-Association-for-Computational-Linguistics (EACL), APR 19-23, 2021, ELECTR NETWORK
Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Volume 1, Long Papers, 2388-2402
STARTPAGE=2388;ENDPAGE=2402;TITLE=Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Volume 1, Long Papers
EACL

Written language contains stylistic cues that can be exploited to automatically infer a variety of potentially sensitive author information. Adversarial stylometry intends to attack such models by rewriting an author's text. Our research proposes sev

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0829988ed098f4fd03e74f149117e297
https://github.com/cmry/reap

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Towards Replication in Computational Cognitive Modeling: A Machine Learning Perspective

Autor: Travis J. Wiltshire, Chris Emmery, Andrew T. Hendrickson, Ákos Kádár

The suggestions proposed by Lee et al. to improve cognitive modeling practices have significant parallels to the current best practices for improving reproducibility in the field of Machine Learning. In the current commentary on `Robust modeling in c

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f46cd190852531cda0a56813dbe9c10a
https://doi.org/10.31234/osf.io/9y72b

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Style Obfuscation by Invariance

Autor: Chris Emmery, Enrique Manjavacas, Grzegorz Chrupała

Publikováno v: Proceedings of the 27th International Conference on Computational Linguistics
COLING 2018
Tilburg University-PURE

The task of obfuscating writing style using sequence models has previously been investigated under the framework of obfuscation-by-transfer, where the input text is explicitly rewritten in another style. These approaches also often lead to major alte

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c04261e3d867cb39f8d2fb45a0e51e0c
http://arxiv.org/abs/1805.07143

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Simple Queries as Distant Labels for Predicting Gender on Twitter

Autor: Grzegorz Chrupała, Chris Emmery, Walter Daelemans

Publikováno v: NUT@EMNLP

The majority of research on extracting missing user attributes from social media profiles use costly hand-annotated labels for supervised learning. Distantly supervised methods exist, although these generally rely on knowledge gathered using external

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::ae3cf4002841b90814457f4e74306eaf
https://doi.org/10.18653/v1/w17-4407

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Evaluating Unsupervised Dutch Word Embeddings as a Linguistic Resource

Autor: Stéphan Tulkens, Chris Emmery, Walter Daelemans

Publikováno v: Evaluating Unsupervised Dutch Word Embeddings as a Linguistic Resource
Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC 2016) / Calzolari, Nicoletta [edit.]; et al.
Scopus-Elsevier
Tilburg University-PURE

Word embeddings have recently seen a strong increase in interest as a result of strong performance gains on a variety of tasks. However, most of this research also underlined the importance of benchmark datasets, and the difficulty of constructing th

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::840efa2ad650d0fa2ea479d1323815b8
https://research.tilburguniversity.edu/en/publications/85d85154-462b-439e-b488-b55671d62ed2

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