Reader-aware Writing Assistance through Reader Profiles

Establishing rapport between authors and readers of scientific texts is essential for supporting readers in understanding texts as intended, facilitating socio-discursive practices within disciplinary communities, and helping in identifying interdisciplinary links among scientific writings.We propose a Reader-aware Congruence Assistant (RaCA), which supports writers to create texts that are adapted to target readers. Similar to user-centered design which is based on user profiles, RaCA features reader-centered writing through reader profiles that are dynamically computed from information discovered through academic search engines. Our assistant then leverages large language models to measure the congruence of a written text with a given reader profile, and provides feedback to the writer. We demonstrate our approach with an implemented prototype that illustrates how RaCA exploits information available on the Web to construct reader profiles, assesses writer-reader congruence and offers writers color-coded visual feedback accordingly. We argue that our approach to reader-oriented scientific writing paves the way towards the more personalized interaction of readers and writers with scientific content, and discuss how integration with Semantic Web technologies and Adaptive User Interface design can help materialize this vision within an ever-growing Web of scientific ideas, proof, and discourse.

Ge Li, Danai Vachtsevanou, Jérémy Lemée, Simon Mayer, and Jannis Strecker. 2024.2024. Reader-aware Writing Assistance through Reader Profiles. In 34th ACM Conference on Hypertext and Social Media (HT ’24), September 10–13, 2024, Poznań, Poland. ACM, New York, NY, USA, 7 pages.