detalle del documento
IDENTIFICACIÓN

oai:arXiv.org:2410.03866

Tema
Computer Science - Human-Computer ...
Autor
Kelly, Christopher Fontanez, Jonatan Sharot, Tali
Categoría

Computer Science

Año

2024

fecha de cotización

9/10/2024

Métrico

Resumen

Search engine results often misalign with users' goals due to opaque algorithms, leading to unhelpful or detrimental information consumption.

To address this, we developed a Google Chrome plugin that provides "content labels" for webpages in Google search results, assessing Actionability (guiding actions), Knowledge (enhancing understanding), and Emotion.

Using natural language processing and machine learning, the plugin predicts these properties from webpage text based on models trained on participants' ratings, effectively reflecting user perceptions.

The implications include enhanced user control over information consumption and promotion of healthier engagement with online content, potentially improving decision-making and well-being.

Kelly, Christopher,Fontanez, Jonatan,Sharot, Tali, 2024, A Tool to Facilitate Web-Browsing

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