You Tweet What You Eat: Studying Food Consumption Through Twitter
By Sofiane Abbar, Yelena Mejova, Ingmar Weber. 2014
255 citations recorded by the source corpus.
Food is an integral part of our lives, cultures, and well-being, and is of major interest to public health. The collection of daily nutritional data involves keeping detailed diaries or periodic surveys and is limited in scope and reach. Alternatively, social media is infamous for allowing its users to update the world on the minutiae of their daily lives, including their eating habits. In this work we examine the potential of Twitter to provide insight into US-wide dietary choices by linking the tweeted dining experiences of 210K users to their interests, demographics, and social networks. We validate our approach by relating the caloric values of the foods mentioned in the tweets to the state-wide obesity rates, achieving a Pearson correlation of 0.77 across the 50 US states and the District of Columbia. We then build a model to predict county-wide obesity and diabetes statistics based on a combination of demographic variables and food names mentioned on Twitter. Our results show significant improvement over previous CHI research (Culotta 2014). We further link this data to societal and economic factors, such as education and income, illustrating that areas with higher education levels tweet about food that is significantly less caloric. Finally, we address the somewhat controversial issue of the social nature of obesity (Christakis & Fowler 2007) by inducing two social networks using mentions and reciprocal following relationships.
Subfields: Communication, Health, Sociology and Political Science
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Communication
- Alexandra Olteanu
- Fernando Diaz
- Carlos Castillo
- Emre Kıcıman
- Isaac L. Johnson
- Johannes Schöning
- Subhasree Sengupta
- Onur Varol
In Health
In Sociology and Political Science
- Alexandra Olteanu
- Fernando Diaz
- Carlos Castillo
- Emre Kıcıman
- Isaac L. Johnson
- Johannes Schöning
- Subhasree Sengupta
- Karl Aberer
Citations in the corpus
- Social Data: Biases, Methodological Pitfalls, and Ethical Boundaries (2019, background): “…assume that co-occurring patterns reflect true relationships, a common task being the extraction of associations among dataset variables (e.g., sources and types of information Olteanu et al., 2015) or with “offline” variables (e.g., food mentions on social media and obesity rates Abbar et al., 2015).”
- Distilling the Outcomes of Personal Experiences: A Propensity-scored Analysis of Social Media (2017, background): “They talk about work or relations [33, 41], health and dietary practices [1, 93], and even log information about their illnesses and coping strategies [23, 34].”
- The Geography and Importance of Localness in Geotagged Social Media (2016, background): “Indeed, researchers in HCI (e.g., [1,9,45,50]), the social sciences (e.g., [10,14,21,39,46,51]), and even the natural sciences (e.g., [38,44,49]) now regularly use social media VGI to better understand phenomena of interest ranging from social unrest and emergencies [6,24,43] to disease tracking…”
- Comparing Events Coverage in Online News and Social Media: The Case of Climate Change (2015, background): “Comparative research (Esser and Hanitzsch 2012) of Twitter communications includes studies on hashtag lifecycles (Lehmann et al. 2012), usage across users of different languages (Hong, Convertino, and Chi 2011), or food consumption (Abbar, Mejova, and Weber 2015).”