Factions Within, Uncertain Across: Within-Document Reader Sub-Groups in Social Highlighting

• URL: http://arxiv.org/abs/2606.11613v1
• Date: Wed, 10 Jun 2026 03:25:36 GMT
• Title: Factions Within, Uncertain Across: Within-Document Reader Sub-Groups in Social Highlighting
• Abstract summary: We ask the group-level question on a co-readership platform using a margin-preserving curveball null.<n>Experiment 1 shows readers form strong sub-groups far beyond what shared salience, mark density, and sentence popularity predict.<n>Experiment 2 is that grouping a stable reader trait? Here we are honest about power.
• Score: 1.8620637029128544
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: When many people highlight the same document, is the crowd a single consensus, or is it internally structured into reader sub-groups that mark different things -- and is that structure a stable property of a reader or of the document? Building on prior work showing an individual's within-document highlighting signal is a whisper while individuality lives in selection, we ask the group-level question on a co-readership platform using a margin-preserving curveball null. Experiment 1: within a document, readers form strong sub-groups -- pairs agree far beyond what shared salience, mark density, and sentence popularity predict (nearest-neighbour agreement z=+6.3, significant in 88% of documents). Under an eight-block region-preserving null, shared engagement with the same coarse regions of the document accounts for about 40% of this excess; the majority survives as finer reader-specific agreement (z=+3.6, 77% significant). So the within-document crowd is, in a descriptive sense, factional. Experiment 2: is that grouping a stable reader trait? Here we are honest about power. The cross-document split-half reproducibility of a pair's agreement is near zero pooled (+0.078 and 0.000 in two separately drawn samples), and a power calibration shows the test is informative only for pairs that co-read many documents. In the only informative high-overlap subset (k>=4), point estimates are positive but small-sample, imprecise across the separately drawn samples, never significant, and attenuate under the region-preserving null. We therefore leave cross-document stability unresolved: the data is consistent with anything from situational grouping to a weak-to-moderate stable reader trait. The crowd is factional within a document; whether its factions follow the reader across documents is, honestly, beyond our reach.

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