DramatVis Personae: Visual Text Analytics for Identifying Social Biases in Creative Writing

TL;DR

This paper introduces DramatVis Personae, a visual analytics tool designed to help writers identify and manage social biases in creative writing by visualizing character identities and their representation.

Contribution

The paper presents a novel visual analytics tool, DVP, that aids writers in detecting and mitigating implicit social biases in their stories, based on interviews and user studies.

Findings

DVP is easy-to-use and integrates naturally into writing workflows.

Writers using DVP can identify biases more efficiently than with a simple text editor.

Participants found DVP helpful for bias detection tasks.

Abstract

Implicit biases and stereotypes are often pervasive in different forms of creative writing such as novels, screenplays, and children's books. To understand the kind of biases writers are concerned about and how they mitigate those in their writing, we conducted formative interviews with nine writers. The interviews suggested that despite a writer's best interest, tracking and managing implicit biases such as a lack of agency, supporting or submissive roles, or harmful language for characters representing marginalized groups is challenging as the story becomes longer and complicated. Based on the interviews, we developed DramatVis Personae (DVP), a visual analytics tool that allows writers to assign social identities to characters, and evaluate how characters and different intersectional social identities are represented in the story. To evaluate DVP, we first conducted think-aloud sessions with three writers and found that DVP is easy-to-use, naturally integrates into the writing process, and could potentially help writers in several critical bias identification tasks. We then conducted a follow-up user study with 11 writers and found that participants could answer questions related to bias detection more efficiently using DVP in comparison to a simple text editor.