Computational Analysis of Storylines: Making sense of events

Tommaso Caselli* (Editor), Eduard Hovy (Editor), Martha Palmer (Editor), Piek Vossen (Editor)

*Corresponding author for this work

Research output: Book/ReportBookAcademicpeer-review

Abstract

Event structures are central in Linguistics and Artificial Intelligence research: people can easily refer to changes in the world, identify their participants, distinguish relevant information, and have expectations of what can happen next. Part of this process is based on mechanisms similar to narratives, which are at the heart of information sharing. But it remains difficult to automatically detect events or automatically construct stories from such event representations. This book explores how to handle today's massive news streams and provides multidimensional, multimodal, and distributed approaches, like automated deep learning, to capture events and narrative structures involved in a 'story'. This overview of the current state-of-the-art on event extraction, temporal and casual relations, and storyline extraction aims to establish a new multidisciplinary research community with a common terminology and research agenda. Graduate students and researchers in natural language processing, computational linguistics, and media studies will benefit from this book.
Original languageEnglish
Place of PublicationNew York, USA
PublisherCambridge University Press
Number of pages260
ISBN (Electronic)9781108854221
ISBN (Print)9781108490573
DOIs
Publication statusPublished - Nov-2021

Publication series

NameStudies in Natural Language Processing
PublisherCambridge University Press

Keywords

  • Discourse analysis
  • Narrative
  • natural language processing
  • storylines

Cite this