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We study the novel problem of finding new, prominent situational facts, which are emerging statements about objects that stand out within certain contexts. Many such facts are newsworthy—e.g., an athlete's outstanding performance in a game, or a viral video's impressive popularity. Effective and efficient identification of these facts assists journalists in reporting, one of the main goals of computational...
Recent years have witnessed an unprecedented proliferation of social media, e.g., millions of blog posts, micro-blog posts, and social networks on the Internet. This kind of social media data can be modeled in a large graph where nodes represent the entities and edges represent relationships between entities of the social media. Discovering keyword-based correlated networks of these large graphs is...
Modern social networks such as Twitter provide a platform for people to express their opinions on a variety of topics ranging from personal to global. While the factual part of this information and the opinions of various experts are archived by sources such as Wikipedia and reputable news articles, the opinion of the general public is drowned out in a sea of noise and “un-interesting” information...
Large-scale text data research has recently started to regain momentum [1]–[10], because of the wealth of up to date information communicated in unstructured format. For example, new information in online media (e.g. Web blogs, Twitter, Facebook, news feeds, etc) becomes instantly available and is refreshed regularly, has very broad coverage and other valuable properties unusual for other data sources...
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