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dc.contributor.authorCASELLI Tommasoen_GB
dc.contributor.authorVAN ERP Mariekeen_GB
dc.contributor.authorMINARD Anne-Lyseen_GB
dc.contributor.authorFINLAYSON Marken_GB
dc.contributor.authorMILLER Benen_GB
dc.contributor.authorATSERIAS Jordien_GB
dc.contributor.authorBALAHUR-DOBRESCU ALEXANDRAen_GB
dc.contributor.authorVOSSEN Pieken_GB
dc.description.abstractThis volume contains the proceedings of the 1st Workshop on Computing News Storylines (CNewsStory 2015) held in conjunction with the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (ACL-IJCNLP 2015) at the China National Convention Center in Beijing, on July 31st 2015. Narratives are at the heart of information sharing. Ever since people began to share their experiences, they have connected them to form narratives. The study od storytelling and the field of literary theory called narratology have developed complex frameworks and models related to various aspects of narrative such as plots structures, narrative embeddings, characters’ perspectives, reader response, point of view, narrative voice, narrative goals, and many others. These notions from narratology have been applied mainly in Artificial Intelligence and to model formal semantic approaches to narratives (e.g. Plot Units developed by Lehnert (1981)). In recent years, computational narratology has qualified as an autonomous field of study and research. Narrative has been the focus of a number of workshops and conferences (AAAI Symposia, Interactive Storytelling Conference (ICIDS), Computational Models of Narrative). Furthermore, reference annotation schemes for narratives have been proposed (NarrativeML by Mani (2013)). The workshop aimed at bringing together researchers from different communities working on representing and extracting narrative structures in news, a text genre which is highly used in NLP but which has received little attention with respect to narrative structure, representation and analysis. Currently, advances in NLP technology have made it feasible to look beyond scenario-driven, atomic extraction of events from single documents and work towards extracting story structures from multiple documents, while these documents are published over time as news streams. Policy makers, NGOs, information specialists (such as journalists and librarians) and others are increasingly in need of tools that support them in finding salient stories in large amounts of information to more effectively implement policies, monitor actions of “big players” in the society and check facts. Their tasks often revolve around reconstructing cases either with respect to specific entities (e.g. person or organizations) or events (e.g. hurricane Katrina). Storylines represent explanatory schemas that enable us to make better selections of relevant information but also projections to the future. They form a valuable potential for exploiting news data in an innovative way.en_GB
dc.description.sponsorshipJRC.G.2-Global security and crisis managementen_GB
dc.publisherAssociation for Computational Linguisticsen_GB
dc.titleProceedings of the First Workshop on Computing News Storylines (CNewsStory 2015)en_GB
JRC Directorate:Space, Security and Migration

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