Project Description
Market Need 
• In the modern online media landscape, there are often a wide range of articles from different media sources covering the same topic.
• For busy web users who wish to obtain a quick view on a topic, it can be difficult to evaluate the best article to read.
Technology Solution
We have developed a number of measures spread over three complementary dimensions
for automatically assessing article quality.
- Authority: This dimension takes into account the reputation of the source of the article along with its level of domain expertise and specificity.
- Social Signal: Multiple measures derived from social interaction ranging from share counts to the relative level of expertise of sharers.
- Content: Ranking and evaluating articles based on their readaibility, depth of coverage and content similarity to similar articles.
Applicability
•Based on a human evaluation over a sample set of articles, the optimum measures and weights for assessing article quality can be learned.
• The technology can be used in areas such as content recommendation and news aggregation and filtering.
Research Team
•Dr. Gerard Lynch, UCD School of Computer Science and Informatics
•Dr. Oisín Boydell, UCD School of Computer Science and Informatics
•Dr. Brian MacNamee, UCD School of Computer Science and Informatics
