short-paper

Spatial and temporal patterns of online food preferences

Authors:

Claudia Wagner,

Philipp Singer,

Markus StrohmaierAuthors Info & Claims

WWW '14 Companion: Proceedings of the 23rd International Conference on World Wide Web

Pages 553 - 554

https://doi.org/10.1145/2567948.2576951

Published: 07 April 2014 Publication History

Get Access

Abstract

Since food is one of the central elements of all human beings, a high interest exists in exploring temporal and spatial food and dietary patterns of humans. Predominantly, data for such investigations stem from consumer panels which continuously capture food consumption patterns from individuals and households. In this work we leverage data from a large online recipe platform which is frequently used in the German speaking regions in Europe and explore (i) the association between geographic proximity and shared food preferences and (ii) to what extent temporal information helps to predict the food preferences of users. Our results reveal that online food preferences of geographically closer regions are more similar than those of distant ones and show that specific types of ingredients are more popular on specific days of the week. The observed patterns can successfully be mapped to known real-world patterns which suggests that existing methods for the investigation of dietary and food patterns (e.g., consumer panels) may benefit from incorporating the vast amount of data generated by users browsing recipes on the Web.

References

[1]

E. N. Anderson. Everyone eats. Understanding food and culture. New York University Press, New York, London, 2005.

Google Scholar

[2]

I. Kiefer, C. Haberzettl, and C. Rieder. Ernahrungsverhalten und einstellung zum essen der österreicherinnen. Journal für Ernahrungsmedizin, 2(5):2--7, 2000.

Google Scholar

[3]

R. West, R. W. White, and E. Horvitz. From cookies to cooks: Insights on dietary patterns via analysis of web usage logs. In Word Wide Web conference (WWW), 2013.

Digital Library

Google Scholar

Cited By

View all

Gligoric KÐordevic IWest R(2022)Biased Bytes: On the Validity of Estimating Food Consumption from Digital TracesProceedings of the ACM on Human-Computer Interaction10.1145/35556606:CSCW2(1-27)Online publication date: 11-Nov-2022
https://dl.acm.org/doi/10.1145/3555660
Jauho MPääkkönen JIsotalo VPöyry ELaaksonen S(2021)How do trendy diets emerge? An exploratory social media study on the low-carbohydrate diet in FinlandFood, Culture & Society10.1080/15528014.2021.197143626:2(344-369)Online publication date: 20-Sep-2021
https://doi.org/10.1080/15528014.2021.1971436
Matsui AKobayashi TMoriwaki DFerrara E(2020)Detecting multi-timescale consumption patterns from receipt data: a non-negative tensor factorization approachJournal of Computational Social Science10.1007/s42001-020-00078-56:2(1179-1192)Online publication date: 20-Aug-2020
https://doi.org/10.1007/s42001-020-00078-5
Show More Cited By

Index Terms

Spatial and temporal patterns of online food preferences
1. Human-centered computing
  1. Collaborative and social computing
    1. Collaborative and social computing systems and tools
2. Information systems
  1. World Wide Web

Recommendations

Kissing Cuisines: Exploring Worldwide Culinary Habits on the Web
WWW '17 Companion: Proceedings of the 26th International Conference on World Wide Web Companion

As food and nutrition occupy an increasingly prevalent space on the web, dishes and recipes shared online provide an invaluable mirror into culinary cultures and attitudes around the world. More specifically, ingredients, flavors, and nutrition ...
Practical food journaling
UbiComp '13 Adjunct: Proceedings of the 2013 ACM conference on Pervasive and ubiquitous computing adjunct publication

Logging dietary intake has been shown to be of benefit to individuals and health researchers, but a practical and objective system for food logging remains elusive despite decades of research. My thesis is that emerging wearable devices such as life-...
Estimating nutritional value from food images based on semantic segmentation
UbiComp '14 Adjunct: Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing: Adjunct Publication

Estimating the nutritional value of food based on image recognition is important to health support services employing mobile devices. The estimation accuracy can be improved by recognizing regions of food objects and ingredients contained in those ...

Comments

Information & Contributors

Information

Published In

WWW '14 Companion: Proceedings of the 23rd International Conference on World Wide Web

April 2014

1396 pages

ISBN:9781450327459

DOI:10.1145/2567948

General Chair:
Chin-Wan Chung
Korea Advanced Institute of Science and Technology, Korea
,
Program Chairs:
Andrei Broder
Google Inc., USA
,
Kyuseok Shim
Seoul National University, Korea
,
Torsten Suel
New York University, USA

In-Cooperation

SIGWEB: ACM Special Interest Group on Hypertext, Hypermedia, and Web

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 07 April 2014

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Short-paper

Conference

WWW '14

Sponsor:

IW3C2

WWW '14: 23rd International World Wide Web Conference

April 7 - 11, 2014

Seoul, Korea

Acceptance Rates

Overall Acceptance Rate 1,899 of 8,196 submissions, 23%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

13
Total Citations
View Citations
321
Total Downloads

Downloads (Last 12 months)3
Downloads (Last 6 weeks)0

Reflects downloads up to 01 Mar 2025

Other Metrics

View Author Metrics

Citations

Cited By

View all

Gligoric KÐordevic IWest R(2022)Biased Bytes: On the Validity of Estimating Food Consumption from Digital TracesProceedings of the ACM on Human-Computer Interaction10.1145/35556606:CSCW2(1-27)Online publication date: 11-Nov-2022
Jauho MPääkkönen JIsotalo VPöyry ELaaksonen S(2021)How do trendy diets emerge? An exploratory social media study on the low-carbohydrate diet in FinlandFood, Culture & Society10.1080/15528014.2021.197143626:2(344-369)Online publication date: 20-Sep-2021
Matsui AKobayashi TMoriwaki DFerrara E(2020)Detecting multi-timescale consumption patterns from receipt data: a non-negative tensor factorization approachJournal of Computational Social Science10.1007/s42001-020-00078-56:2(1179-1192)Online publication date: 20-Aug-2020
Asano YBiermann G(2019)Rising adoption and retention of meat-free diets in online recipe dataNature Sustainability10.1038/s41893-019-0316-02:7(621-627)Online publication date: 1-Jul-2019
Pantidi NSelinas PFlintham MBaurley SRodden TBrereton M(2017)Bread storiesProceedings of the 29th Australian Conference on Computer-Human Interaction10.1145/3152771.3152788(152-161)Online publication date: 28-Nov-2017
Sajadmanesh SJafarzadeh SOssia SRabiee HHaddadi HMejova YMusolesi MCristofaro EStringhini GBarrett RCummings RAgichtein EGabrilovich E(2017)Kissing CuisinesProceedings of the 26th International Conference on World Wide Web Companion10.1145/3041021.3055137(1013-1021)Online publication date: 3-Apr-2017
De Choudhury MKumar MWeber ILee CPoltrock SBarkhuus LBorges MKellogg W(2017)Computational Approaches Toward Integrating Quantified Self Sensing and Social MediaProceedings of the 2017 ACM Conference on Computer Supported Cooperative Work and Social Computing10.1145/2998181.2998219(1334-1349)Online publication date: 25-Feb-2017
Sanjo SKatsurai M(2017)Towards recommending diverse seasonal cooking recipes: A preliminary study based on monthly view data2017 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT)10.1109/ISSPIT.2017.8388660(306-310)Online publication date: Dec-2017
Lee CPoltrock SBarkhuus LBorges MKellogg W(2017)Proceedings of the 2017 ACM Conference on Computer Supported Cooperative Work and Social ComputingundefinedOnline publication date: 25-Feb-2017
De Choudhury MSharma SKiciman EGergle DMorris MBjørn PKonstan J(2016)Characterizing Dietary Choices, Nutrition, and Language in Food Deserts via Social MediaProceedings of the 19th ACM Conference on Computer-Supported Cooperative Work & Social Computing10.1145/2818048.2819956(1157-1170)Online publication date: 27-Feb-2016
Show More Cited By

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Abstract

References

Cited By

Index Terms

Recommendations

Kissing Cuisines: Exploring Worldwide Culinary Habits on the Web

Practical food journaling

Estimating nutritional value from food images based on semantic segmentation

Comments

Information

Published In

Sponsors

In-Cooperation

Publisher

Publication History

Permissions

Check for updates

Author Tags

Qualifiers

Conference

Acceptance Rates

Contributors

Other Metrics

Bibliometrics

Article Metrics

Other Metrics

Citations

Cited By

Login options

Full Access

View options

PDF

eReader

Share

Share this Publication link

Share on social media

Affiliations