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DeepDive, a newest product of the Times' development team beta620, offers a separate interface that allows its users to read related articles based on a particular date or topic. The goal, according to the DeepDive website, is to enable users to follow story arcs and identify topics they wish to follow.
At launch, DeepDive filters content using the Times' existing framework of topical tagging. The sample root article on DeepDive site "Yemeni President’s Loyalists Blamed in Deaths of Protesters," for example, is tagged "Middle East and North Africa Unrest (2010- )" and "Demonstrations, Protests, and Riots." In the future, however, Times' developers hope to expand to semantic, editorial, and social tagging as well.
At NewsCred, however, we take philosophy of DeepDive a step further. Every day, our API filters and customizes news articles by topic, location, language, source, and date. Along with the resources of our world-class editorial team, NewsCred uses proprietary semantic and NLP technology to curate 215,000 full-text articles from 751 sources (and growing), across 50 countries, in 8 languages, organized into 20 categories and 47,000 topics. That's a deep dive even Steve Zissou, the protagonist of Wes Anderson's film The Life Aquatic, would be jealous of.