CLIP Colloquium: Naeemul Hasan (Journalism/iSchool)

Naeemul Hasan (Assistant Professor, Journalism & Information Sciences)

Towards Automated Fact Discovery and Ranking

Abstract: In this talk, I present the work 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 journalism. A situational fact can be modeled as a “contextual” tuple that stands out against historical tuples in a context, specified by a conjunctive constraint involving dimension attributes when a set of measure attributes are compared. New tuples are constantly added to the table, reflecting events happening in the real world. Our goal is to discover constraint-measure pairs that qualify a new tuple as a contextual significant tuple, and discover them quickly before the event becomes yesterday’s news.