KAIST Computer Science, South Korea
SUMMARY:
This paper discusses a web service called NewsCube. NewsCube aims to mitigate the effects of media bias. They are the first know experiment to tackle the problem computationally. They mention they can reduce bias, but underlying causes make it impossible to eliminate bias. Look at the picture below to see how news gets from reality to print.
Some groups such as fair.org, NewsTrust.net, and skewz.com have tried to serve as watchdog groups on media bias. Problem is these news is usually immediate and can't wait for user reviews. NewsCube focuses on letting the user develop their own view on media bias.
NewsCube uses news structure-based extraction which involves classifying bias of a news article based on the aspect the author is writing the story from. For example, a news article could state Obama passes health care. While an article on the same topic from a different aspect might say McCain criticizes Obama's health care plan. NewsCube aims to distinguish the two views and present both of them to the user.
The authors claimed that NewsCube was effective. They stated they were planning on incorporating it as a service with a major internet news company in Korea.
DISCUSSION:
It is hard to evaluate NewsCube without actually using it but according to the study it works. The main problem is that there is no perfect algorithm for evaluating bias on a news article with an undefined subject. However, this product still interests me since I believe at critical times mainstream news can often be very biased.
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