arXiv Open Access 2018

Utilizing a Transparency-driven Environment toward Trusted Automatic Genre Classification: A Case Study in Journalism History

Aysenur Bilgin Laura Hollink Jacco van Ossenbruggen Erik Tjong Kim Sang Kim Smeenk +2 lainnya

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Abstrak

With the growing abundance of unlabeled data in real-world tasks, researchers have to rely on the predictions given by black-boxed computational models. However, it is an often neglected fact that these models may be scoring high on accuracy for the wrong reasons. In this paper, we present a practical impact analysis of enabling model transparency by various presentation forms. For this purpose, we developed an environment that empowers non-computer scientists to become practicing data scientists in their own research field. We demonstrate the gradually increasing understanding of journalism historians through a real-world use case study on automatic genre classification of newspaper articles. This study is a first step towards trusted usage of machine learning pipelines in a responsible way.

Topik & Kata Kunci

cs.CL cs.LG

Penulis (7)

Aysenur Bilgin

Laura Hollink

Jacco van Ossenbruggen

Erik Tjong Kim Sang

Kim Smeenk

Frank Harbers

Marcel Broersma

Format Sitasi

APA MLA BibTeX

Bilgin, A., Hollink, L., Ossenbruggen, J.v., Sang, E.T.K., Smeenk, K., Harbers, F. et al. (2018). Utilizing a Transparency-driven Environment toward Trusted Automatic Genre Classification: A Case Study in Journalism History. https://arxiv.org/abs/1810.00968

Akses Cepat

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Informasi Jurnal

Tahun Terbit: 2018
Bahasa: en
Sumber Database: arXiv
Akses: Open Access ✓