Text Visualization and Close Reading for Journalism with Storifier

Nicole Sultanum, Anastasia Bezerianos, Fanny Chevalier

View presentation:2021-10-27T13:40:00ZGMT-0600Change your timezone on the schedule page
2021-10-27T13:40:00Z
Exemplar figure, described by caption below
A screenshot of the user interface of Storifier, overlaid by the title of the work (Text Visualization and Close Reading for Journalism with Storifier) and by the URL of the system (storifier.cs.toronto.edu).
Keywords

Social Science, Education, Humanities, Journalism, Intelligence Analysis, Knowledge Work, Charts, Diagrams, and Plots, Coordinated and Multiple Views, Multi-Resolution and Level of Detail Techniques, Data Analysis, Reasoning, Problem Solving, and Decision Making, Application Motivated Visualization, Deployment, Human-Subjects Qualitative Studies, Text/Document Data

Abstract

Journalistic inquiry often requires analysis and close study of large text collections around a particular topic. We argue that this practice could benefit from a more text- and reading-centered approach to journalistic text analysis, one that allows for a fluid transition between overview of entities of interest, the context of these entities in the text, down to the detailed documents they are extracted from. We present the design and development process of Storifier, informed by a close collaboration with a large francophone news office. We also discuss a case study on how our tool was used to analyze a text collection and publish a story.