Document detail
ID
oai:arXiv.org:2410.03866
Topic
Computer Science - Human-Computer ...Author
Kelly, Christopher Fontanez, Jonatan Sharot, TaliCategory
Computer Science
Year
2024
listing date
10/9/2024
Abstract
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
Systematic Feature Design for Cycle Life Prediction of Lithium-Ion Batteries During Formation
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