Interacting with Literary Style through Computational Tools

要旨

Style is an important aspect of writing, shaping how audiences interpret and engage with literary works. However, for most people style is difficult to articulate precisely. While users frequently interact with computational word processing tools with well-defined metrics, such as spelling and grammar checkers, style is a significantly more nuanced concept. In this paper, we present a computational technique to help surface style in written text. We collect a dataset of crowdsourced human judgments of style, derive a model of style by training a neural net on this data, and present novel applications for visualizing and browsing style across broad bodies of literature, as well as an interactive text editor with real-time style feedback. We study these interactive style applications with users and discuss implications for enabling this novel approach to style.

キーワード
Creativity Support
Humanities
Text/Speech/Language
Artifact or System
著者
Sarah Sterman
University of California, Berkeley, Berkeley, CA, USA
Evey Huang
University of California, Berkeley, Berkeley, CA, USA
Vivian Liu
University of California, Berkeley, Berkeley, CA, USA
Eric Paulos
University of California, Berkeley, Berkeley, CA, USA
DOI

10.1145/3313831.3376730

動画

会議: CHI 2020

The ACM CHI Conference on Human Factors in Computing Systems

セッション: Tools & interfaces

Paper session
Paper
313C O'AHU
2020-04-28 01:00:00
2020-04-28 02:15:00
日本語まとめ
読み込み中…