From Cookies to Cooks: Insights on Dietary Patterns via Analysis of Web
Usage Logs
R. West, R. White, and E. Horvitz. (2013)cite arxiv:1304.3742Comment: WWW 2013, 11 pages, 11 figures.
Abstract
Nutrition is a key factor in people's overall health. Hence, understanding
the nature and dynamics of population-wide dietary preferences over time and
space can be valuable in public health. To date, studies have leveraged small
samples of participants via food intake logs or treatment data. We propose a
complementary source of population data on nutrition obtained via Web logs. Our
main contribution is a spatiotemporal analysis of population-wide dietary
preferences through the lens of logs gathered by a widely distributed
Web-browser add-on, using the access volume of recipes that users seek via
search as a proxy for actual food consumption. We discover that variation in
dietary preferences as expressed via recipe access has two main periodic
components, one yearly and the other weekly, and that there exist
characteristic regional differences in terms of diet within the United States.
In a second study, we identify users who show evidence of having made an acute
decision to lose weight. We characterize the shifts in interests that they
express in their search queries and focus on changes in their recipe queries in
particular. Last, we correlate nutritional time series obtained from recipe
queries with time-aligned data on hospital admissions, aimed at understanding
how behavioral data captured in Web logs might be harnessed to identify
potential relationships between diet and acute health problems. In this
preliminary study, we focus on patterns of sodium identified in recipes over
time and patterns of admission for congestive heart failure, a chronic illness
that can be exacerbated by increases in sodium intake.
Description
From Cookies to Cooks: Insights on Dietary Patterns via Analysis of Web
Usage Logs
%0 Conference Paper
%1 west2013cookies
%A West, Robert
%A White, Ryen W.
%A Horvitz, Eric
%D 2013
%K analysis log nutrition www2013
%T From Cookies to Cooks: Insights on Dietary Patterns via Analysis of Web
Usage Logs
%U http://www2013.org/proceedings/p1399.pdf
%X Nutrition is a key factor in people's overall health. Hence, understanding
the nature and dynamics of population-wide dietary preferences over time and
space can be valuable in public health. To date, studies have leveraged small
samples of participants via food intake logs or treatment data. We propose a
complementary source of population data on nutrition obtained via Web logs. Our
main contribution is a spatiotemporal analysis of population-wide dietary
preferences through the lens of logs gathered by a widely distributed
Web-browser add-on, using the access volume of recipes that users seek via
search as a proxy for actual food consumption. We discover that variation in
dietary preferences as expressed via recipe access has two main periodic
components, one yearly and the other weekly, and that there exist
characteristic regional differences in terms of diet within the United States.
In a second study, we identify users who show evidence of having made an acute
decision to lose weight. We characterize the shifts in interests that they
express in their search queries and focus on changes in their recipe queries in
particular. Last, we correlate nutritional time series obtained from recipe
queries with time-aligned data on hospital admissions, aimed at understanding
how behavioral data captured in Web logs might be harnessed to identify
potential relationships between diet and acute health problems. In this
preliminary study, we focus on patterns of sodium identified in recipes over
time and patterns of admission for congestive heart failure, a chronic illness
that can be exacerbated by increases in sodium intake.
@inproceedings{west2013cookies,
abstract = {Nutrition is a key factor in people's overall health. Hence, understanding
the nature and dynamics of population-wide dietary preferences over time and
space can be valuable in public health. To date, studies have leveraged small
samples of participants via food intake logs or treatment data. We propose a
complementary source of population data on nutrition obtained via Web logs. Our
main contribution is a spatiotemporal analysis of population-wide dietary
preferences through the lens of logs gathered by a widely distributed
Web-browser add-on, using the access volume of recipes that users seek via
search as a proxy for actual food consumption. We discover that variation in
dietary preferences as expressed via recipe access has two main periodic
components, one yearly and the other weekly, and that there exist
characteristic regional differences in terms of diet within the United States.
In a second study, we identify users who show evidence of having made an acute
decision to lose weight. We characterize the shifts in interests that they
express in their search queries and focus on changes in their recipe queries in
particular. Last, we correlate nutritional time series obtained from recipe
queries with time-aligned data on hospital admissions, aimed at understanding
how behavioral data captured in Web logs might be harnessed to identify
potential relationships between diet and acute health problems. In this
preliminary study, we focus on patterns of sodium identified in recipes over
time and patterns of admission for congestive heart failure, a chronic illness
that can be exacerbated by increases in sodium intake.},
added-at = {2013-08-02T17:29:36.000+0200},
author = {West, Robert and White, Ryen W. and Horvitz, Eric},
biburl = {https://www.bibsonomy.org/bibtex/2b67d4ef3c31b782897ff23821b84207f/schwemmlein},
description = {From Cookies to Cooks: Insights on Dietary Patterns via Analysis of Web
Usage Logs},
interhash = {c9aa0b7aa3beb9da25d5713671e5b3fb},
intrahash = {b67d4ef3c31b782897ff23821b84207f},
keywords = {analysis log nutrition www2013},
note = {cite arxiv:1304.3742Comment: WWW 2013, 11 pages, 11 figures},
timestamp = {2013-08-02T17:29:36.000+0200},
title = {From Cookies to Cooks: Insights on Dietary Patterns via Analysis of Web
Usage Logs},
url = {http://www2013.org/proceedings/p1399.pdf},
year = 2013
}