AI & ML
Embedding User Comments into Long-Form Reading: Design and Evaluation of Contextual Comment Presentation
arXiv cs.HC0 views
arXiv:2512.06408v4 Announce Type: replace Abstract: Online comments offer perspectives on long-form articles but are often separated from the passages they discuss, requiring readers to navigate back and forth and mentally reconstruct comment-text relationships. To preserve these relationships while maintaining reading continuity, we explored contextual comment presentation that makes comments locally accessible at the passages they address. We compared Text-End, Sentence-End, Between-Line, and Click-to-Show in a within-subject study with 24 participants using constructed comments and fixed sentence-level anchors. All three local layouts reduced initial-reading scrolling, with no significant condition effects on accuracy or elapsed task time. Sentence-End and Between-Line received higher comment-accessibility ratings than Text-End, while Click-to-Show received higher physical-demand ratings than Text-End and Sentence-End. Preferences remained distributed across all four layouts.
Source:https://arxiv.org/abs/2512.06408PreviousDull, Dirty, Dangerous? Working Conditions and the Limits of Occupational AI ExposureNextSmell with Genji: Rediscovering Sensory Experience with an AI Co-Smelling Partner
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