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Autori principali: Welsh, Ben, Zhou, Naitian, Kaz, Arda, Vu, Michael, Spangher, Alexander
Natura: Preprint
Pubblicazione: 2024
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Accesso online:https://arxiv.org/abs/2501.00004
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author Welsh, Ben
Zhou, Naitian
Kaz, Arda
Vu, Michael
Spangher, Alexander
author_facet Welsh, Ben
Zhou, Naitian
Kaz, Arda
Vu, Michael
Spangher, Alexander
contents Information prioritization plays an important role in how humans perceive and understand the world. Homepage layouts serve as a tangible proxy for this prioritization. In this work, we present NewsHomepages, a large dataset of over 3,000 new website homepages (including local, national and topic-specific outlets) captured twice daily over a three-year period. We develop models to perform pairwise comparisons between news items to infer their relative significance. To illustrate that modeling organizational hierarchies has broader implications, we applied our models to rank-order a collection of local city council policies passed over a ten-year period in San Francisco, assessing their "newsworthiness". Our findings lay the groundwork for leveraging implicit organizational cues to deepen our understanding of information prioritization.
format Preprint
id arxiv_https___arxiv_org_abs_2501_00004
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle NewsHomepages: Homepage Layouts Capture Information Prioritization Decisions
Welsh, Ben
Zhou, Naitian
Kaz, Arda
Vu, Michael
Spangher, Alexander
Information Retrieval
Artificial Intelligence
Computation and Language
Information prioritization plays an important role in how humans perceive and understand the world. Homepage layouts serve as a tangible proxy for this prioritization. In this work, we present NewsHomepages, a large dataset of over 3,000 new website homepages (including local, national and topic-specific outlets) captured twice daily over a three-year period. We develop models to perform pairwise comparisons between news items to infer their relative significance. To illustrate that modeling organizational hierarchies has broader implications, we applied our models to rank-order a collection of local city council policies passed over a ten-year period in San Francisco, assessing their "newsworthiness". Our findings lay the groundwork for leveraging implicit organizational cues to deepen our understanding of information prioritization.
title NewsHomepages: Homepage Layouts Capture Information Prioritization Decisions
topic Information Retrieval
Artificial Intelligence
Computation and Language
url https://arxiv.org/abs/2501.00004