skip to main content
10.1145/3526113.3545672acmconferencesArticle/Chapter ViewAbstractPublication PagesuistConference Proceedingsconference-collections
research-article

Beyond Text Generation: Supporting Writers with Continuous Automatic Text Summaries

Authors Info & Claims
Published:28 October 2022Publication History

ABSTRACT

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.

References

  1. Ahmed Sabbir Arif, Sunjun Kim, Wolfgang Stuerzlinger, Geehyuk Lee, and Ali Mazalek. 2016. Evaluation of a Smart-Restorable Backspace Technique to Facilitate Text Entry Error Correction. In Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems (San Jose, California, USA) (CHI ’16). Association for Computing Machinery, New York, NY, USA, 5151–5162. https://doi.org/10.1145/2858036.2858407Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. Kenneth C Arnold, April M Volzer, and Noah G Madrid. 2021. Generative Models can Help Writers without Writing for Them. 2nd Workshop on Human-AI Co-Creation with Generative Models - HAI-GEN 2021 (2021), 8.Google ScholarGoogle Scholar
  3. Michel Beaudouin-Lafon, Susanne Bødker, and Wendy E. Mackay. 2021. Generative Theories of Interaction. ACM Trans. Comput.-Hum. Interact. 28, 6, Article 45 (nov 2021), 54 pages. https://doi.org/10.1145/3468505Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. Daniel Buschek, Martin Zürn, and Malin Eiband. 2021. The Impact of Multiple Parallel Phrase Suggestions on Email Input and Composition Behaviour of Native and Non-Native English Writers. In Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems (Yokohama, Japan) (CHI ’21). Association for Computing Machinery, New York, NY, USA, Article 732, 13 pages. https://doi.org/10.1145/3411764.3445372Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. Hakan Ceylan and Rada Mihalcea. 2009. The Decomposition of Human-Written Book Summaries. In Computational Linguistics and Intelligent Text Processing, Alexander Gelbukh (Ed.). Vol. 5449. Springer Berlin Heidelberg, Berlin, Heidelberg, 582–593. https://doi.org/10.1007/978-3-642-00382-0_47 Series Title: Lecture Notes in Computer Science.Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. Mia Xu Chen, Benjamin N. Lee, Gagan Bansal, Yuan Cao, Shuyuan Zhang, Justin Lu, Jackie Tsay, Yinan Wang, Andrew M. Dai, Zhifeng Chen, Timothy Sohn, and Yonghui Wu. 2019. Gmail Smart Compose: Real-Time Assisted Writing. In Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (Anchorage, AK, USA) (KDD ’19). Association for Computing Machinery, New York, NY, USA, 2287–2295. https://doi.org/10.1145/3292500.3330723Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. John Joon Young Chung, Wooseok Kim, Kang Min Yoo, Hwaran Lee, Eytan Adar, and Minsuk Chang. 2022. TaleBrush: Sketching Stories with Generative Pretrained Language Models. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, Vol. CHI’22. Association for Computing Machinery, New Orleans, LA, USA, 19.Google ScholarGoogle Scholar
  8. Elizabeth Clark, Anne Spencer Ross, Chenhao Tan, Yangfeng Ji, and Noah A. Smith. 2018. Creative Writing with a Machine in the Loop: Case Studies on Slogans and Stories. In 23rd International Conference on Intelligent User Interfaces (Tokyo, Japan) (IUI ’18). Association for Computing Machinery, New York, NY, USA, 329–340. https://doi.org/10.1145/3172944.3172983Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. Juliet M Corbin. 1990. Basics of qualitative research: Grounded theory procedures and techniques. Sage.Google ScholarGoogle Scholar
  10. Andy Cresswell. 2000. Self-monitoring in student writing: developing learner responsibility. ELT Journal 54, 3 (July 2000), 235–244. https://doi.org/10.1093/elt/54.3.235Google ScholarGoogle ScholarCross RefCross Ref
  11. Wenzhe Cui, Suwen Zhu, Mingrui Ray Zhang, H. Andrew Schwartz, Jacob O. Wobbrock, and Xiaojun Bi. 2020. JustCorrect: Intelligent Post Hoc Text Correction Techniques on Smartphones. Association for Computing Machinery, New York, NY, USA, 487–499. https://doi.org/10.1145/3379337.3415857Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. Linda Flower and John R Hayes. 1981. A cognitive process theory of writing. College composition and communication 32, 4 (1981), 365–387.Google ScholarGoogle ScholarCross RefCross Ref
  13. Katy Ilonka Gero and Lydia B. Chilton. 2019. Metaphoria: An Algorithmic Companion for Metaphor Creation. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems (Glasgow, Scotland Uk) (CHI ’19). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3290605.3300526Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. Marjan Ghazvininejad, Xing Shi, Jay Priyadarshi, and Kevin Knight. 2017. Hafez: an Interactive Poetry Generation System. In Proceedings of ACL 2017, System Demonstrations. Association for Computational Linguistics, Vancouver, Canada, 43–48. https://www.aclweb.org/anthology/P17-4008Google ScholarGoogle ScholarCross RefCross Ref
  15. Aaron Hamburger. 2013. Outlining in Reverse. https://opinionator.blogs.nytimes.com/2013/01/21/outlining-in-reverse/ Cad: 1 Section: Opinion.Google ScholarGoogle Scholar
  16. Han L. Han, Miguel A. Renom, Wendy E. Mackay, and Michel Beaudouin-Lafon. 2020. Textlets: Supporting Constraints and Consistency in Text Documents. Association for Computing Machinery, New York, NY, USA, 1–13. https://doi.org/10.1145/3313831.3376804Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. Forrest Huang, Eldon Schoop, David Ha, and John Canny. 2020. Scones: Towards Conversational Authoring of Sketches. In Proceedings of the 25th International Conference on Intelligent User Interfaces (Cagliari, Italy) (IUI ’20). Association for Computing Machinery, New York, NY, USA, 313–323. https://doi.org/10.1145/3377325.3377485Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. Anjuli Kannan, Karol Kurach, Sujith Ravi, Tobias Kaufmann, Andrew Tomkins, Balint Miklos, Greg Corrado, Laszlo Lukacs, Marina Ganea, Peter Young, and Vivek Ramavajjala. 2016. Smart Reply: Automated Response Suggestion for Email. In Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (San Francisco, California, USA) (KDD ’16). Association for Computing Machinery, New York, NY, USA, 955–964. https://doi.org/10.1145/2939672.2939801Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. Cynthia L. King. 2012. Reverse Outlining: A Method for Effective Revision of Document Structure. IEEE Transactions on Professional Communication 55, 3 (Sept. 2012), 254–261. https://doi.org/10.1109/TPC.2012.2207838 Conference Name: IEEE Transactions on Professional Communication.Google ScholarGoogle ScholarCross RefCross Ref
  20. Wojciech Kryscinski, Nitish Shirish Keskar, Bryan McCann, Caiming Xiong, and Richard Socher. 2019. Neural Text Summarization: A Critical Evaluation. In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, 540–551. https://doi.org/10.18653/v1/D19-1051Google ScholarGoogle Scholar
  21. Purdue Writing Lab. 2021. Reverse Outlining // Purdue Writing Lab. https://owl.purdue.edu/owl/general_writing/the_writing_process/reverse_outlining.htmlGoogle ScholarGoogle Scholar
  22. Mina Lee, Percy Liang, and Qian Yang. 2022. CoAuthor: Designing a Human-AI Collaborative Writing Dataset for Exploring Language Model Capabilities. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems(CHI’22). Association for Computing Machinery, New Orleans, LA, USA. https://doi.org/10.1145/3491102.3502030Google ScholarGoogle ScholarDigital LibraryDigital Library
  23. Luis A. Leiva. 2018. Responsive text summarization. Inform. Process. Lett. 130 (2018), 52–57. https://doi.org/10.1016/j.ipl.2017.10.007Google ScholarGoogle ScholarCross RefCross Ref
  24. Karen Sheriff LeVan and Marissa E King. 2017. Self-Annotation as a Course Practice. Teaching English in the Two Year College 44, 3 (2017), 289.Google ScholarGoogle Scholar
  25. Daniel Li, Thomas Chen, Albert Tung, and Lydia B Chilton. 2021. Hierarchical Summarization for Longform Spoken Dialog. In The 34th Annual ACM Symposium on User Interface Software and Technology (Virtual Event, USA) (UIST ’21). Association for Computing Machinery, New York, NY, USA, 582–597. https://doi.org/10.1145/3472749.3474771Google ScholarGoogle ScholarDigital LibraryDigital Library
  26. Yang Li, Sayan Sarcar, Sunjun Kim, and Xiangshi Ren. 2020. Swap: A Replacement-Based Text Revision Technique for Mobile Devices. Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3313831.3376217Google ScholarGoogle ScholarDigital LibraryDigital Library
  27. Nina Macdonald, Lawrence Frase, P Gingrich, and Stacey Keenan. 1982. The writer’s workbench: Computer aids for text analysis. IEEE Transactions on Communications 30, 1 (1982), 105–110.Google ScholarGoogle ScholarCross RefCross Ref
  28. Kristin Messuri. 2016. Revision Strategies. The Southwest Respiratory and Critical Care Chronicles 4, 14 (April 2016), 46–48. https://pulmonarychronicles.com/index.php/pulmonarychronicles/article/view/263 Number: 14.Google ScholarGoogle Scholar
  29. Kristin Messuri. 2016. Writing Effective Paragraphs. The Southwest Respiratory and Critical Care Chronicles 4, 15 (July 2016), 86–88. https://pulmonarychronicles.com/index.php/pulmonarychronicles/article/view/290 Number: 15.Google ScholarGoogle ScholarCross RefCross Ref
  30. Rada Mihalcea and Paul Tarau. 2004. Textrank: Bringing order into text. In Proceedings of the 2004 conference on empirical methods in natural language processing. 404–411.Google ScholarGoogle Scholar
  31. Michael J. Muller and Sandra Kogan. 2012. Grounded Theory Method in Human-Computer Interaction and Computer-Supported Cooperative Work. In The Human–Computer Interaction Handbook (3 ed.). CRC Press. Num Pages: 21.Google ScholarGoogle Scholar
  32. Graduate Writing Center of the Center for Excellence in Writing. 2007. Strategies for Drafting & Revising Academic Writing. https://www.tnstate.edu/write/documents/DraftingRevisingEves2007.pdfGoogle ScholarGoogle Scholar
  33. University of Wisconsin-Madison. 2021. Reverse Outlines: A Writer’s Technique for Examining Organization. https://writing.wisc.edu/wp-content/uploads/sites/535/2018/07/reverseoutlines_uwmadison_writingcenter_aug2012.pdfGoogle ScholarGoogle Scholar
  34. Sam Park. 2008. Reverse Outlining Worksheet | Student Learning Center. https://slc.berkeley.edu/writing-worksheets-and-other-writing-resources/reverse-outlining-worksheetGoogle ScholarGoogle Scholar
  35. Dragomir R. Radev, Eduard Hovy, and Kathleen McKeown. 2002. Introduction to the Special Issue on Summarization. Computational Linguistics 28, 4 (Dec. 2002), 399–408. https://doi.org/10.1162/089120102762671927Google ScholarGoogle ScholarDigital LibraryDigital Library
  36. Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J. Liu. 2020. Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer. arXiv:1910.10683 [cs, stat] (July 2020). http://arxiv.org/abs/1910.10683 arXiv:1910.10683.Google ScholarGoogle Scholar
  37. Jeba Rezwana and Mary Lou Maher. 2022. Designing Creative AI Partners with COFI: A Framework for Modeling Interaction in Human-AI Co-Creative Systems. ACM Trans. Comput.-Hum. Interact. (feb 2022). https://doi.org/10.1145/3519026 Just Accepted.Google ScholarGoogle ScholarDigital LibraryDigital Library
  38. Melissa Roemmele and Andrew S Gordon. 2015. Creative help: A story writing assistant. In International Conference on Interactive Digital Storytelling. Springer, 81–92.Google ScholarGoogle ScholarCross RefCross Ref
  39. Laura Saltz. 1998. Harvard College Writing Center - Revising the Draft. https://writingcenter.fas.harvard.edu/pages/revising-draftGoogle ScholarGoogle Scholar
  40. Oliver Schmitt and Daniel Buschek. 2021. CharacterChat: Supporting the Creation of Fictional Characters through Conversation and Progressive Manifestation with a Chatbot. In Creativity and Cognition (Virtual Event, Italy) (C&C ’21). Association for Computing Machinery, New York, NY, USA, Article 10, 10 pages. https://doi.org/10.1145/3450741.3465253Google ScholarGoogle ScholarDigital LibraryDigital Library
  41. Abigail See, Peter Liu, and Christopher Manning. 2017. Get To The Point: Summarization with Pointer-Generator Networks. In Association for Computational Linguistics. https://arxiv.org/abs/1704.04368Google ScholarGoogle Scholar
  42. Nikhil Singh, Guillermo Bernal, Daria Savchenko, and Elena L. Glassman. 2022. Where to Hide a Stolen Elephant: Leaps in Creative Writing with Multimodal Machine Intelligence. ACM Trans. Comput.-Hum. Interact. (jan 2022). https://doi.org/10.1145/3511599 Just Accepted.Google ScholarGoogle ScholarDigital LibraryDigital Library
  43. Carola Strobl, Emilie Ailhaud, Kalliopi Benetos, Ann Devitt, Otto Kruse, Antje Proske, and Christian Rapp. 2019. Digital support for academic writing: A review of technologies and pedagogies. Computers & Education 131 (2019), 33–48. https://doi.org/10.1016/j.compedu.2018.12.005Google ScholarGoogle ScholarCross RefCross Ref
  44. Hariharan Subramonyam, Colleen Seifert, Priti Shah, and Eytan Adar. 2020. TexSketch: Active Diagramming through Pen-and-Ink Annotations. Association for Computing Machinery, New York, NY, USA, 1–13. https://doi.org/10.1145/3313831.3376155Google ScholarGoogle ScholarDigital LibraryDigital Library
  45. Reid Swanson and Andrew S Gordon. 2008. Say anything: A massively collaborative open domain story writing companion. In Joint International Conference on Interactive Digital Storytelling. Springer, 32–40.Google ScholarGoogle ScholarDigital LibraryDigital Library
  46. Pradyumna Tambwekar, Murtaza Dhuliawala, Lara J. Martin, Animesh Mehta, Brent Harrison, and Mark O. Riedl. 2018. Controllable Neural Story Plot Generation via Reinforcement Learning. arxiv:1809.10736 [cs.CL]Google ScholarGoogle Scholar
  47. Maartje ter Hoeve, Robert Sim, Elnaz Nouri, Adam Fourney, Maarten de Rijke, and Ryen W. White. 2020. Conversations with Documents: An Exploration of Document-Centered Assistance. In Proceedings of the 2020 Conference on Human Information Interaction and Retrieval(Vancouver BC, Canada) (CHIIR ’20). Association for Computing Machinery, New York, NY, USA, 43–52. https://doi.org/10.1145/3343413.3377971Google ScholarGoogle ScholarDigital LibraryDigital Library
  48. L. Danielle Tully. 2019. Reverse Outlines: Fueling Revision & Preparing for Writing Conferences. The Second Draft 32, 2 (2019), 6. https://ssrn.com/abstract=3465807Google ScholarGoogle Scholar
  49. Duke University. 2021. Revising Process | Thompson Writing Program. https://twp.duke.edu/sites/twp.duke.edu/files/file-attachments/reverse-outline.original.pdfGoogle ScholarGoogle Scholar
  50. Keith Vertanen, Mark Dunlop, James Clawson, Per Ola Kristensson, and Ahmed Sabbir Arif. 2016. Inviscid Text Entry and Beyond. In Proceedings of the 2016 CHI Conference Extended Abstracts on Human Factors in Computing Systems (San Jose, California, USA) (CHI EA ’16). Association for Computing Machinery, New York, NY, USA, 3469–3476. https://doi.org/10.1145/2851581.2856472Google ScholarGoogle ScholarDigital LibraryDigital Library
  51. Keith Vertanen, Kyle Montague, Mark Dunlop, Ahmed Sabbir Arif, Xiaojun Bi, and Shiri Azenkot. 2017. Ubiquitous Text Interaction. In Proceedings of the 2017 CHI Conference Extended Abstracts on Human Factors in Computing Systems (Denver, Colorado, USA) (CHI EA ’17). Association for Computing Machinery, New York, NY, USA, 566–573. https://doi.org/10.1145/3027063.3027066Google ScholarGoogle ScholarDigital LibraryDigital Library
  52. Bryan Wang, Gang Li, Xin Zhou, Zhourong Chen, Tovi Grossman, and Yang Li. 2021. Screen2words: Automatic mobile UI summarization with multimodal learning. In The 34th Annual ACM Symposium on User Interface Software and Technology. 498–510.Google ScholarGoogle ScholarDigital LibraryDigital Library
  53. Harriet Salatas Waters and Wolfgang Schneider. 2009. Metacognition, Strategy Use, and Instruction. Guilford Press.Google ScholarGoogle Scholar
  54. Daijin Yang, Yanpeng Zhou, Zhiyuan Zhang, and Toby Jia-Jun Li. 2022. AI as an Active Writer: Interaction strategies with generated text in human-AI collaborative fiction writing. In IUI 2022 Workshop on Human-AI Co-Creation with Generative Models (HAI-GEN 2022). 10.Google ScholarGoogle Scholar
  55. Qian Yang, Justin Cranshaw, Saleema Amershi, Shamsi T. Iqbal, and Jaime Teevan. 2019. Sketching NLP: A Case Study of Exploring the Right Things To Design with Language Intelligence. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems (Glasgow, Scotland Uk) (CHI ’19). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3290605.3300415Google ScholarGoogle ScholarDigital LibraryDigital Library
  56. Demet Yaylı. 2012. Tracing the benefits of self annotation in genre-based writing. The Journal of Language Learning and Teaching 2, 1 (2012), 45–58.Google ScholarGoogle Scholar
  57. Ann Yuan, Andy Coenen, Emily Reif, and Daphne Ippolito. 2022. Wordcraft: Story Writing With Large Language Models. In 27th International Conference on Intelligent User Interfaces(IUI ’22). Association for Computing Machinery, New York, NY, USA, 841–852. https://doi.org/10.1145/3490099.3511105Google ScholarGoogle ScholarDigital LibraryDigital Library
  58. Mingrui Ray Zhang, He Wen, and Jacob O. Wobbrock. 2019. Type, Then Correct: Intelligent Text Correction Techniques for Mobile Text Entry Using Neural Networks. In Proceedings of the 32nd Annual ACM Symposium on User Interface Software and Technology (New Orleans, LA, USA) (UIST ’19). Association for Computing Machinery, New York, NY, USA, 843–855. https://doi.org/10.1145/3332165.3347924Google ScholarGoogle ScholarDigital LibraryDigital Library

Index Terms

  1. Beyond Text Generation: Supporting Writers with Continuous Automatic Text Summaries

        Recommendations

        Comments

        Login options

        Check if you have access through your login credentials or your institution to get full access on this article.

        Sign in
        • Published in

          cover image ACM Conferences
          UIST '22: Proceedings of the 35th Annual ACM Symposium on User Interface Software and Technology
          October 2022
          1363 pages
          ISBN:9781450393201
          DOI:10.1145/3526113

          Copyright © 2022 ACM

          Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

          Publisher

          Association for Computing Machinery

          New York, NY, United States

          Publication History

          • Published: 28 October 2022

          Permissions

          Request permissions about this article.

          Request Permissions

          Check for updates

          Qualifiers

          • research-article
          • Research
          • Refereed limited

          Acceptance Rates

          Overall Acceptance Rate842of3,967submissions,21%

          Upcoming Conference

          UIST '24

        PDF Format

        View or Download as a PDF file.

        PDF

        eReader

        View online with eReader.

        eReader

        HTML Format

        View this article in HTML Format .

        View HTML Format