Entity-oriented materials and opinions extraction from news articles
○許 レイ,切通恵介,馬  強,吉川正俊(京大)
For detecting the inconsistency and alerting the bias in news contents, we propose a method of extracting materials and opinions from news articles.
We extract materials and opinions by 1) classifying entity-related phrases into objective and subjective descriptions, and 2) discovering opinion holders in subjective descriptions. The extracted materials and opinions help us construct the Material-opinion Model for difference analysis of news contents.
A prototype system is implemented and we also show some experimental results to validate the proposed methods.

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