Storyteller: Visual Analytics of Perspectives on Rich Text Interpretations

Maarten van Meersbergen, Piek Vossen, Janneke van der Zwaan, Antske Fokkens, Willem van Hage, Inger Leemans, Isa Maks


Abstract
Complexity of event data in texts makes it difficult to assess its content, especially when considering larger collections in which different sources report on the same or similar situations. We present a system that makes it possible to visually analyze complex event and emotion data extracted from texts. We show that we can abstract from different data models for events and emotions to a single data model that can show the complex relations in four dimensions. The visualization has been applied to analyze 1) dynamic developments in how people both conceive and express emotions in theater plays and 2) how stories are told from the perspectyive of their sources based on rich event data extracted from news or biographies.
Anthology ID:
W17-4207
Volume:
Proceedings of the 2017 EMNLP Workshop: Natural Language Processing meets Journalism
Month:
September
Year:
2017
Address:
Copenhagen, Denmark
Editors:
Octavian Popescu, Carlo Strapparava
Venue:
WS
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
37–45
Language:
URL:
https://aclanthology.org/W17-4207
DOI:
10.18653/v1/W17-4207
Bibkey:
Cite (ACL):
Maarten van Meersbergen, Piek Vossen, Janneke van der Zwaan, Antske Fokkens, Willem van Hage, Inger Leemans, and Isa Maks. 2017. Storyteller: Visual Analytics of Perspectives on Rich Text Interpretations. In Proceedings of the 2017 EMNLP Workshop: Natural Language Processing meets Journalism, pages 37–45, Copenhagen, Denmark. Association for Computational Linguistics.
Cite (Informal):
Storyteller: Visual Analytics of Perspectives on Rich Text Interpretations (van Meersbergen et al., 2017)
Copy Citation:
PDF:
https://aclanthology.org/W17-4207.pdf