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Beyond Text Generation : Supporting Writers with Continuous Automatic Text Summaries

Title data

Dang, Hai ; Benharrak, Karim ; Lehmann, Florian ; Buschek, Daniel:
Beyond Text Generation : Supporting Writers with Continuous Automatic Text Summaries.
2022
Event: ACM Symposium on User Interface Software and Technology , 29.10. - 02.11.2022 , Bend, Oregon, USA.
(Conference item: Conference , Paper )
DOI: https://doi.org/10.1145/3526113.3545672

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Project information

Project title:
Project's official titleProject's id
AI Tools - Continuous Interaction with Computational Intelligence ToolsNo information

Abstract in another language

We propose a text editor to help users plan, structure and reflect on their writing process. It provides continuously updated paragraph-wise summaries as margin annotations, using automatic text summarization. Summary levels range from full text, to selected (central) sentences, down to a collection of keywords. To understand how users interact with this system during writing, we conducted two user studies (N=4 and N=8) in which people wrote analytic essays about a given topic and article. As a key finding, the summaries gave users an external perspective on their writing and helped them to revise the content and scope of their drafted paragraphs. People further used the tool to quickly gain an overview of the text and developed strategies to integrate insights from the automated summaries. More broadly, this work explores and highlights the value of designing AI tools for writers, with Natural Language Processing (NLP) capabilities that go beyond direct text generation and correction.

Further data

Item Type: Conference item (Paper)
Refereed: Yes
Additional notes: https://osf.io/v6zfn/
code, dataset
Keywords: text documents; text summarization; semantic zoom; reverse outlining; Natural Language Processing
Institutions of the University: Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Computer Science
Faculties
Faculties > Faculty of Mathematics, Physics und Computer Science
Result of work at the UBT: Yes
DDC Subjects: 000 Computer Science, information, general works > 004 Computer science
Date Deposited: 25 Aug 2022 07:21
Last Modified: 25 Aug 2022 07:21
URI: https://eref.uni-bayreuth.de/id/eprint/71673