arXiv — NLP / Computation & Language · · 4 min read

Trait, Not State: The Durability of Reading Identity in Social Highlighting

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Computer Science > Information Retrieval

arXiv:2606.12904 (cs)
[Submitted on 11 Jun 2026]

Title:Trait, Not State: The Durability of Reading Identity in Social Highlighting

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Abstract:Prior work on a social web highlighter located individuality in selection -- which documents a person chooses to highlight -- but measured it cross-sectionally. We ask the temporal question: is a reader's selection signature a trait or a state? We freeze each reader's first six months of highlighting as a profile and track its own-vs-other advantage on their later selections at growing gaps (to 24+ months), with negatives drawn from the same calendar era -- so supply drift cannot masquerade as personal drift -- at a coarse global level and at a fine level whose negatives and controls come from the reader's own interest neighborhood; the anchor cell reproduces the prior cross-sectional level (+0.188 vs +0.169), validating the harness. Four results. Within the same users, the fine-layer advantage shows no statistically detectable paired decline at any horizon (6-12 month retention R = 1.00 [0.85, 1.18], n = 212; the farthest bin is compatible with a modest decline; the only contrast whose interval excludes zero is the coarse layer at 12-24 months, about 13%). The signal is not reducible to repeated domains (~90% survives excluding all profile sources). Within-person drift is slow (a recent-half profile beats the old half by +0.042). Prospectively, personal profiles -- even one built from a reader's earliest documents, median 20 months before evaluation -- rank their next reads at roughly 3x the AP of every simple non-personal prior tested. We use "trait" operationally (a stable signature under continued engagement); the scope is heavy, long-tenured readers of one platform, and exposure is not separable from choice.
Comments: 12 pages, 3 figures, 3 tables
Subjects: Information Retrieval (cs.IR); Computation and Language (cs.CL); Human-Computer Interaction (cs.HC); Social and Information Networks (cs.SI)
Cite as: arXiv:2606.12904 [cs.IR]
  (or arXiv:2606.12904v1 [cs.IR] for this version)
  https://doi.org/10.48550/arXiv.2606.12904
arXiv-issued DOI via DataCite (pending registration)

Submission history

From: Kazuki Nakayashiki [view email]
[v1] Thu, 11 Jun 2026 04:59:37 UTC (49 KB)
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