クラウドソーシングを用いたニュース記事の偏った文章の表示と分析
Annotating and Analyzing Biased Sentences in News Articles using Crowdsourcing

概要

News bias has become an challenging issue for a long time in the society. Even though initial approaches towards automatically detecting bias in news articles have been developed, there is lack of a suitable ground truth for such a task. In this research, we propose a novel dataset created with the help of crowd-sourcing for fostering research on bias detection and removal from news content.

産業界への展開例・適用分野

This research can be applied for fostering bias detection and removal from news content. In addition, it can be applied for subjective and relative labeling tasks with achieving high quality labels.

研究者

氏名 専攻 研究室 役職/学年
Lim Sora 社会情報学専攻 Yoshikawa-Ma Lab. 博士3回生
Adam Jatowt 社会情報学専攻 Yoshikawa-Ma Lab. 特定准教授
Yoshikawa Masatoshi 社会情報学専攻 Yoshikawa-Ma Lab. 教授

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