The Impact of Recipe Features, Social Cues and Demographics on Estimating the Healthiness of Online Recipes

Twelfth International Conference on Web and Social Media, ICWSM 2018, Stanford, California, USA, June 25-28, 2018

[1]  A. Pentland,et al.  Life in the network: The coming age of computational social science: Science , 2009 .

[2]  Brian Wansink,et al.  Mindless Eating , 2006 .

[3]  M L Neuhouser,et al.  Use of food nutrition labels is associated with lower fat intake. , 1999, Journal of the American Dietetic Association.

[4]  Judith Masthoff,et al.  A Survey of Explanations in Recommender Systems , 2007, 2007 IEEE 23rd International Conference on Data Engineering Workshop.

[5]  Markus Strohmaier,et al.  Ieee Intelligent Systems Computational Social Science for the World Wide Web Computational Social Science , 2022 .

[6]  David Elsweiler,et al.  Ingredient matching to determine the nutritional properties of Internet-sourced recipes , 2012, 2012 6th International Conference on Pervasive Computing Technologies for Healthcare (PervasiveHealth) and Workshops.

[7]  Paul Geladi,et al.  Principal Component Analysis , 1987, Comprehensive Chemometrics.

[8]  Catherine A. Cole,et al.  Consumers' Search and Use of Nutrition Information: The Challenge and Promise of the Nutrition Labeling and Education Act , 2002 .

[9]  Ani Nenkova,et al.  Revisiting Readability: A Unified Framework for Predicting Text Quality , 2008, EMNLP.

[10]  Sofiane Abbar,et al.  You Tweet What You Eat: Studying Food Consumption Through Twitter , 2014, CHI.

[11]  Amaia Salvador,et al.  Learning Cross-Modal Embeddings for Cooking Recipes and Food Images , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[12]  Susan A. Jebb,et al.  Estimating food portions. Influence of unit number, meal type and energy density☆☆☆☆ , 2013, Appetite.

[13]  J. Wardle,et al.  Development of a Measure of the Motives Underlying the Selection of Food: the Food Choice Questionnaire , 1995, Appetite.

[14]  Albert-László Barabási,et al.  Flavor network and the principles of food pairing , 2011, Scientific reports.

[15]  George Loewenstein,et al.  Strategies for Promoting Healthier Food Choices. , 2009, The American economic review.

[16]  Henry Agnew,et al.  Evaluating the Impact of Menu Labeling on Food Choices and Intake , 2022 .

[17]  Christoph Trattner,et al.  Investigating the Healthiness of Internet-Sourced Recipes: Implications for Meal Planning and Recommender Systems , 2017, WWW.

[18]  Michael I. Jordan,et al.  Latent Dirichlet Allocation , 2001, J. Mach. Learn. Res..

[19]  Julie A. Caswell,et al.  Toward a More Comprehensive Theory of Food Labels , 1992 .

[20]  Daniel Fried,et al.  Analyzing the language of food on social media , 2014, 2014 IEEE International Conference on Big Data (Big Data).

[21]  Munmun De Choudhury,et al.  Characterizing Dietary Choices, Nutrition, and Language in Food Deserts via Social Media , 2016, CSCW.

[22]  B. Elbel,et al.  Child and adolescent fast-food choice and the influence of calorie labeling: a natural experiment , 2011, International Journal of Obesity.

[23]  Andrew Zisserman,et al.  Very Deep Convolutional Networks for Large-Scale Image Recognition , 2014, ICLR.

[24]  Yukinobu Taniguchi,et al.  Estimating nutritional value from food images based on semantic segmentation , 2014, UbiComp Adjunct.

[25]  Shady Elbassuoni,et al.  Calories Prediction from Food Images , 2017, AAAI.

[26]  Douglas E Levy,et al.  A traffic light food labeling intervention increases consumer awareness of health and healthy choices at the point-of-purchase. , 2013, Preventive medicine.

[27]  Kjetil Nørvåg,et al.  Online Food Recipe Title Semantics: Combining Nutrient Facts and Topics , 2016, CIKM.

[28]  Ryen W. White,et al.  From cookies to cooks: insights on dietary patterns via analysis of web usage logs , 2013, WWW.

[29]  Bill Tomlinson,et al.  Who are the crowdworkers?: shifting demographics in mechanical turk , 2010, CHI Extended Abstracts.

[30]  Christoph Trattner,et al.  Plate and Prejudice: Gender Differences in Online Cooking , 2016, UMAP.

[31]  Sergio Guadarrama,et al.  Im2Calories: Towards an Automated Mobile Vision Food Diary , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).

[32]  Shervin Shirmohammadi,et al.  A Novel SVM Based Food Recognition Method for Calorie Measurement Applications , 2012, 2012 IEEE International Conference on Multimedia and Expo Workshops.

[33]  Christoph Trattner,et al.  How Editorial, Temporal and Social Biases Affect Online Food Popularity and Appreciation , 2017, ICWSM.

[34]  Jennifer Erickson,et al.  Total, Added, and Free Sugars: Are Restrictive Guidelines Science-Based or Achievable? , 2015, Nutrients.

[35]  Scot Burton,et al.  Age, Product Nutrition, and Label Format Effects on Consumer Perceptions and Product Evaluations , 1996 .

[36]  Jonathan J. Fox,et al.  Who uses nutrition labeling, and what effects does label use have on diet quality? , 1995 .

[37]  Christoph Trattner,et al.  Estimating the Healthiness of Internet Recipes: A Cross-sectional Study , 2017, Front. Public Health.

[38]  José San Pedro,et al.  Ranking and classifying attractiveness of photos in folksonomies , 2009, WWW '09.

[39]  R. Carels,et al.  Qualitative perceptions and caloric estimations of healthy and unhealthy foods by behavioral weight loss participants , 2006, Appetite.

[40]  Christoph Trattner,et al.  Exploiting Food Choice Biases for Healthier Recipe Recommendation , 2017, SIGIR.

[41]  Alan Said,et al.  You are What You Eat! Tracking Health Through Recipe Interactions , 2014, RSWeb@RecSys.

[42]  Lynn Stockley,et al.  Consumer understanding and use of nutrition labelling: a systematic review , 2005, Public Health Nutrition.