From Who You Know to What You Read: Augmenting Scientific Recommendations with Implicit Social Networks

Hyeonsu B. Kang, Rafal Kocielnik, Andrew Head, Jiangjiang Yang, Matt Latzke, Aniket Kittur, Daniel S. Weld, Doug Downey, Jonathan Bragg

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The ever-increasing pace of scientific publication necessitates methods for quickly identifying relevant papers. While neural recommenders trained on user interests can help, they still result in long, monotonous lists of suggested papers. To improve the discovery experience we introduce multiple new methods for augmenting recommendations with textual relevance messages that highlight knowledge-graph connections between recommended papers and a user's publication and interaction history. We explore associations mediated by author entities and those using citations alone. In a large-scale, real-world study, we show how our approach significantly increases engagement - and future engagement when mediated by authors - without introducing bias towards highly-cited authors. To expand message coverage for users with less publication or interaction history, we develop a novel method that highlights connections with proxy authors of interest to users and evaluate it in a controlled lab study. Finally, we synthesize design implications for future graph-based messages.

Original languageEnglish (US)
Title of host publicationCHI 2022 - Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems
PublisherAssociation for Computing Machinery
ISBN (Electronic)9781450391573
DOIs
StatePublished - Apr 29 2022
Externally publishedYes
Event2022 CHI Conference on Human Factors in Computing Systems, CHI 2022 - Virtual, Online, United States
Duration: Apr 30 2022May 5 2022

Publication series

NameConference on Human Factors in Computing Systems - Proceedings

Conference

Conference2022 CHI Conference on Human Factors in Computing Systems, CHI 2022
Country/TerritoryUnited States
CityVirtual, Online
Period4/30/225/5/22

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Computer Graphics and Computer-Aided Design
  • Software

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