The First Worskop on Computing News Storylines (CNewS 2015) aims at bringing together researchers and scientists working on narrative extraction and representation from news within Computational Linguistics and Artificial Intelligence. Narratives are at the heart of information sharing. Ever since people began to share their experiences, they have connected them to form narratives. Modern day news reports still reflect this narrative structure, but they have proven difficult for automatic tools to summarise, structure, or connect to other reports. Most text processing tools focus on extracting relatively simple structures from the local lexical environment, and concentrate on the document as a unit or on even smaller units such as sentences or phrases, rather than cross-document connections especially published over longer periods of time. However, current information needs demand a move towards multidimensional and distributed representations which take into account the connections between all relevant elements involved in a “story”. The workshop aims at assessing the state-of-the-art in event extraction and linking, as well as detecting and ranking narratives according to salience. The workshop invites work on all aspects of generating narrative structures or components thereof from news. This includes topics such as (but not limited to): detecting events from news linguistic expression of relevant events filtering relevant events cumulation of information from news streams detecting opinions and perspectives finding trending or serendipitous stories in news tracing perspective change through time modeling plot structures storyline stability and completeness annotating storylines temporal or causal ordering of events linguistics resources for storylines big data as a source for storylines evaluation of storylines discourse structure and storylines visualisation of storylines detecting facts and speculations dynamic event modeling Submissions