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Comprehensive Terms Board Visualization for News Analysis and Editorial Story Planning

Sami, I., Russell-Rose, T. ORCID: 0000-0003-4394-9876 & Soldatova, L. (2022). Comprehensive Terms Board Visualization for News Analysis and Editorial Story Planning. In: CEUR Workshop Proceedings. Sixth Workshop on Narrative Extraction From Texts, 2 Apr 2023, Dublin, Ireland.

Abstract

Knowledge providers, such as authors, teachers, researchers and journalists rely on researching facts to convey evidence-driven information about a selected topic and story planning in the pre-writing phase enhances engagement and understanding of the audience through a better content organization. Typical search engines support finding relevant facts, but they do not aid an individual?s metacognition process of a topic. In this demo, we introduce the concept of the Terms Board, a topic-driven comprehensive visualization for presenting terms to provide a cognitive guide for news analysis and formulating their plans for storytelling in editorial writing. Terms Board is composed of six cards reflecting the major storytelling aspects: what the story is about, who are the characters of the story, where the story is located, why there are challenges, what has been done to address the challenges and why the actions were effective. Each card shows three top terms based on three factual timeline aspects: historical, consistent and latest. For this demo, we extracted emphasised terms from a collection of documents in a news archive and produced a Terms Board for the most frequent topics which were then presented to a group of study participants. Participants? performances on several tasks have been measured and analysed. The study results are encouraging. The major contribution of this research is presenting a Terms Board visualisation approach as a cognitive guide for news analysis and editorial story planning and presenting an experimental evaluation of this approach via cognitive reading and writing user experiment tasks.

Publication Type: Conference or Workshop Item (Paper)
Additional Information: © 2023 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
Publisher Keywords: Natural Language Processing, Visualization, Story Planning, News Writing
Subjects: P Language and Literature
Departments: School of Science & Technology
School of Science & Technology > Computer Science
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